Prediction Of Neurological Outcome Research Articles

External Validation of Updated Prediction Models for Neurological Outcomes at 90 Days in Patients With Out-of-Hospital Cardiac Arrest.

Few prediction models for individuals with early-stage out-of-hospital cardiac arrest (OHCA) have undergone external validation. This study aimed to externally validate updated prediction models for OHCA outcomes using a large nationwide dataset. We performed a secondary analysis of the JAAM-OHCA (Comprehensive Registry of In-Hospital Intensive Care for Out-of-Hospital Cardiac Arrest Survival and the Japanese Association for Acute Medicine Out-of-Hospital Cardiac Arrest) registry. Previously developed prediction models for patients with cardiac arrest who achieved the return of spontaneous circulation were updated. External validation was conducted using data from 56 institutions from the JAAM-OHCA registry. The primary outcome was a dichotomized 90-day cerebral performance category score. Two models were updated using the derivation set (n=3337). Model 1 included patient demographics, prehospital information, and the initial rhythm upon hospital admission; Model 2 included information obtained in the hospital immediately after the return of spontaneous circulation. In the validation set (n=4250), Models 1 and 2 exhibited a C-statistic of 0.945 (95% CI, 0.935-0.955) and 0.958 (95% CI, 0.951-0.960), respectively. Both models were well-calibrated to the observed outcomes. The decision curve analysis showed that Model 2 demonstrated higher net benefits at all risk thresholds than Model 1. A web-based calculator was developed to estimate the probability of poor outcomes (https://pcas-prediction.shinyapps.io/90d_lasso/). The updated models offer valuable information to medical professionals in the prediction of long-term neurological outcomes for patients with OHCA, potentially playing a vital role in clinical decision-making processes.

Plasma glial fibrillary acidic protein and tau: predictors of neurological outcome after cardiac arrest

BackgroundThe purpose was to evaluate glial fibrillary acidic protein (GFAP) and total-tau in plasma as predictors of poor neurological outcome after out-of-hospital (OHCA) and in-hospital cardiac arrest (IHCA), including comparisons with neurofilament light (NFL) and neuron-specific enolase (NSE).MethodsRetrospective multicentre observational study of patients admitted to an intensive care unit (ICU) in three hospitals in Sweden 2014–2018. Blood samples were collected at ICU admission, 12 h, and 48 h post-cardiac arrest. Poor neurological outcome was defined as Cerebral Performance Category 3–5 at 2–6 months after cardiac arrest. Plasma samples were retrospectively analysed for GFAP, tau, and NFL. Serum NSE was analysed in clinical care. Prognostic performances were tested with the area under the receiver operating characteristics curve (AUC).ResultsOf the 428 included patients, 328 were OHCA, and 100 were IHCA. At ICU admission, 12 h and 48 h post-cardiac arrest, GFAP predicted neurological outcome after OHCA with AUC (95% CI) 0.76 (0.70–0.82), 0.86 (0.81–0.90) and 0.91 (0.87–0.96), and after IHCA with AUC (95% CI) 0.77 (0.66–0.87), 0.83 (0.74–0.92) and 0.83 (0.71–0.95). At the same time points, tau predicted outcome after OHCA with AUC (95% CI) 0.72 (0.66–0.79), 0.75 (0.69–0.81), and 0.93 (0.89–0.96) and after IHCA with AUC (95% CI) 0.61 (0.49–0.74), 0.68 (0.56–0.79), and 0.77 (0.65–0.90). Adding the change in biomarker levels between time points did not improve predictive accuracy compared to the last time point. In a subset of patients, GFAP at 12 h and 48 h, as well as tau at 48 h, offered similar predictive value as NSE at 48 h (the earliest time point NSE is recommended in guidelines) after both OHCA and IHCA. The predictive performance of NFL was similar or superior to GFAP and tau at all time points after OHCA and IHCA.ConclusionGFAP and tau are promising biomarkers for neuroprognostication, with the highest predictive performance at 48 h after OHCA, but not superior to NFL. The predictive ability of GFAP may be sufficiently high for clinical use at 12 h after cardiac arrest.

Verbal Glasgow Coma Scale as predictor of persistent disorder of consciousness: Insights for improving accuracy and reliability in clinical practice

This brief report discusses the relationship between verbal function, disorders of consciousness, and neurological follow-up after acute brain injury. It provides valuable insights for improving the accuracy and reliability of Verbal Glasgow Coma Scale scoring in clinical practice. The report addresses the need for standardized training and underlines the importance of physiological stabilization before assessment. Clarity in communication, recognition of non-verbal cues, and serial assessments are emphasized as critical factors to reduce the Verbal Glasgow Coma Scale inconsistencies. It also promotes interdisciplinary collaboration and cultural sensitivity to refine the Verbal Glasgow Coma Scale evaluation, improving the prediction of long-term neurological outcomes after acute brain injury and optimizing effective rehabilitation programs. Possible strategies to implement in the routine clinical practice the provided tips are discussed.

Association between early lactate-related variables and 6-month neurological outcome in out-of-hospital cardiac arrest patients

IntroductionThe role of lactate measurement in out-of-hospital cardiac arrest (OHCA) survivors remains controversial. We assessed the association between early lactate-related variables, OHCA characteristics, and long-term neurological outcome. MethodsIn OHCA patients who received targeted temperature management, lactate levels were measured at 0, 12, and 24 h after the return of spontaneous circulation. We calculated lactate clearance and time-weighted cumulative lactate (TWCL), which represent the area under the time-lactate curve. The area under the receiver operating characteristic curve (AUC) and the adjusted odds ratios (AORs) of lactate-related variables for predicting 6-month poor outcome (Cerebral Performance Category 3–5) were evaluated. Interactions between lactate variables and characteristics of OHCA were evaluated by a multivariable logistic model with interaction terms and subgroup analysis. ResultsA total of 347 OHCA patients were included. After adjustment, higher lactate levels at the three time points were associated with a poor outcome (AOR 1.10 [95% CI, 1.03–1.18], AOR 1.15 [95% CI, 1.02–1.29], and AOR 1.36 [95% CI, 1.15–1.60], respectively), while TWCL was the only lactate kinetics variable associated with a poor outcome (AOR 1.29 [95% CI, 1.12–1.49]). We identified several interactions between lactate-related variables and OHCA characteristics. In particular, the AUC of TWCL was excellent in cases of noncardiac etiology (AUC 0.92 [95% CI, 0.86–0.96] but only moderate in cardiac etiology (AUC 0.69 [95% CI, 0.62–0.75]). ConclusionsEarly lactate levels, especially at 24 h, and TWCL were independent predictors of neurologic outcome in these patients, whereas lactate clearance was not. The prognostic ability of lactate-related variables varied depending on the OHCA characteristics.

Brain Swelling versus Infarct Size: A Problematizing Review.

In human stroke, brain swelling is an important predictor of neurological outcome and mortality, yet treatments to reduce or prevent brain swelling are extremely limited, due in part to an inadequate understanding of mechanisms. In preclinical studies on cerebroprotection in animal models of stroke, historically, the focus has been on reducing infarct size, and in most studies, a reduction in infarct size has been associated with a corresponding reduction in brain swelling. Unfortunately, such findings on brain swelling have little translational value for treating brain swelling in patients with stroke. This is because, in humans, brain swelling usually becomes evident, either symptomatically or radiologically, days after the infarct size has stabilized, requiring that the prevention or treatment of brain swelling target mechanism(s) that are independent of a reduction in infarct size. In this problematizing review, we highlight the often-neglected concept that brain edema and brain swelling are not simply secondary, correlative phenomena of stroke but distinct pathological entities with unique molecular and cellular mechanisms that are worthy of direct targeting. We outline the advances in approaches for the study of brain swelling that are independent of a reduction in infarct size. Although straightforward, the approaches reviewed in this study have important translational relevance for identifying novel treatment targets for post-ischemic brain swelling.

Advanced Magnetic Resonance Imaging Biomarkers of the Injured Spinal Cord: A Comparative Study of Imaging and Histology in Human Traumatic Spinal Cord Injury.

A significant problem in the diagnosis and management of traumatic spinal cord injury (tSCI) is the heterogeneity of secondary injury and the prediction of neurological outcome. Imaging biomarkers specific to myelin loss and inflammation after tSCI would enable detailed assessment of the pathophysiological processes underpinning secondary damage to the cord. Such biomarkers could be used to biologically stratify injury severity and better inform prognosis for neurological recovery. While much work has been done to establish magnetic resonance imaging (MRI) biomarkers for SCI in animal models, the relationship between imaging findings and the underlying pathology has been difficult to discern in human tSCI because of the paucity of human spinal cord tissue. We utilized post-mortem spinal cords from individuals who had a tSCI to examine this relationship by performing ex vivo MRI scans before histological analysis. We investigated the correlation between the histological distribution of myelin loss and inflammatory cells in the injured spinal cord and a number of myelin and inflammation-sensitive MRI measures: myelin water fraction (MWF), inhomogeneous magnetization transfer ratio (ihMTR), and diffusion tensor and diffusion kurtosis imaging-derived fractional anisotropy (FA) and axial, radial, and mean diffusivity (AD, RD, MD). The histological features were analyzed by staining with Luxol Fast Blue (LFB) for myelin lipids and Class II major histocompatibility complex (Class II MHC) and CD68 for microglia and macrophages. Both MWF and ihMTR were strongly correlated with LFB staining for myelin, supporting the use of both as biomarkers for myelin loss after SCI. A decrease in ihMTR was also correlated with the presence of Class II MHC positive immune cells. FA and RD correlated with both Class II MHC and CD68 and may therefore be useful biomarkers for inflammation after tSCI. Our work demonstrates the utility of advanced MRI techniques sensitive to biological tissue damage after tSCI, which is an important step toward using these MRI techniques in the clinic to aid in decision-making.

WITHDRAWN: Malignant transformation of ischemic stroke in the era of mechanical thrombectomy: When is decompressive craniectomy required?

ObjectiveThe treatment of choice for ischemic stroke due to intracranial arterial occlusion of the anterior circulation has been mechanical thrombectomy (MT). The success rate of MT is described as 71%, but malignant infarction can nonetheless ensue. In these cases, decompressive craniectomy (DHC) is often necessary. To date, only few factors are known to correlate significantly with the need for DHC after MT. MethodsWe conducted a retrospective analysis of patients admitted with anterior circulation stroke at our department who underwent MT with and without subsequent DHC. Patients were matched according to ASPECT score on pre-MT CT scan. Established predictors for neurological outcome, TICI grade of recanalization, as well as imaging were then compared between the groups to elucidate which of them were predictive of DHC. ResultsA total of 86 patients were included in the analysis. DHC was performed in 43 patients (50%). In a univariate analysis, male sex (p = 0.037), lower TICI grade of recanalization (p < 0.001) and hemorrhagic transformation (p = 0.014) were predictive of DHC. Patients who received later intravenous thrombolysis were also at higher risk for needing DHC (p = 0.050). Patients suffering from hypercholesterolemia (p < .001) and who were on antiplatlet agents (p = .039) were at lower risk for needing DHC. ConclusionsPatients with higher rates of recanalization were protected against DHC. Later administration of IV tPA was correlated with DHC, thus suggesting a synergistic effect of IV tPA and MT in protecting against malignant transformation. Prior use of antiplatelet agents appears to be a protective factor against DHC in stroke, which warrants further investigation.

The relationship between the initial pH and neurological outcome in patients with out-of-hospital cardiac arrest is affected by the status of recovery of spontaneous circulation on hospital arrival.

The early prediction of neurological outcomes is useful for out-of-hospital cardiac arrest (OHCA). The initial pH was associated with neurological outcomes, but the values varied among the studies. Patients admitted to our division with OHCA of cardiac origin between January 2015 and December 2022 were retrospectively examined (N = 199). A good neurological outcome was defined as a Glasgow-Pittsburgh cerebral performance category (CPC) of 1-2 at discharge. Patients were divided according to the achievement of recovery of spontaneous circulation (ROSC) on hospital arrival, and the efficacy of pH in predicting good neurological outcomes was compared. In patients with ROSC on hospital arrival (N = 100), the initial pH values for good and poor neurological outcomes were 7.26 ± 0.14 and 7.09 ± 0.18, respectively (p < 0.001). In patients without ROSC on hospital arrival (N = 99), the initial pH values for good and poor neurological outcomes were 7.06 ± 0.23 and 6.92 ± 0.15, respectively (p = 0.007). The pH associated with good neurological outcome was much lower in patients without ROSC than in those with ROSC on hospital arrival (P = 0.003). A higher initial pH is associated with good neurological outcomes in patients with OHCA. However, the pH for a good or poor neurological outcome depends on the ROSC status on hospital arrival.

Ferritin as an Effective Predictor of Neurological Outcomes in Children With Acute Necrotizing Encephalopathy

BackgroundAcute necrotizing encephalopathy (ANE) is a fulminant disease with poor prognosis. Cytokine storm is the important phenomenon of ANE that affects the brain and multiple organs. The study aimed to identify whether hyperferritinemia was associated with poor prognosis in patients with ANE. MethodsAll patients with ANE had multiple symmetric lesions located in the bilateral thalami and other regions such as brainstem tegmentum, cerebral white matter, and cerebellum. Neurological outcome at discharge was evaluated by pediatric neurologists using the Pediatric Cerebral Performance Category Scale. All risk factors associated with poor prognosis were further analyzed using receiver operating characteristic curve analysis. ResultsTwenty-nine patients with ANE were enrolled in the current study. Nine (31%) patients achieved a favorable neurological outcome, and 20 (69%) patients had poor neurological outcomes. results The group of poor neurological outcome had significantly higher proportion of shock on admission and brainstem involvement. Based on multivariate logistic regression analysis, ferritin, aspartate aminotransferase (AST), and ANE severity score (ANE-SS) were the predictors associated with outcomes. The appropriate cutoff value for predicting neurological outcomes in patients with ANE was 1823 ng/mL for ferritin, 78 U/L for AST, and 4.5 for ANE-SS. Besides, comparison analyses showed that higher level of ferritin and ANE-SS were significantly correlated with brainstem involvement (P < 0.05). ConclusionsFerritin may potentially be a prognostic factor in patients with ANE. Hyperferritinemia is associated with poor neurological outcomes in patients with ANE and ferritin levels more than 1823 ng/mL have about eightfold increased risk of poor neurological outcome.

Optimal PHASES Scoring for Risk Stratification of Surgically Treated Unruptured Aneurysms

The PHASES (Population, Hypertension, Age, Size, Earlier subarachnoid hemorrhage, Site) score was developed to facilitate risk stratification for management of unruptured intracranial aneurysms (UIAs). This study aimed to identify the optimal PHASES score cutoff for predicting neurologic outcomes in patients with surgically treated aneurysms. All patients who underwent microneurosurgical treatment for UIA at a large quaternary center from January 1, 2014, to December 31, 2020, were retrospectively reviewed. Inclusion criteria included a modified Rankin Scale (mRS) score of ≤2 at admission. The primary outcome was 1-year mRS score, with a "poor" neurologic outcome defined as an mRS score >2. In total, 375 patients were included in the analysis. The mean (SD) PHASES score for the entire study population was 4.47 (2.67). Of 375 patients, 116 (31%) had a PHASES score ≥6, which was found to maximize prediction of poor neurologic outcome. Patients with PHASES scores ≥6 had significantly higher rates of poor neurologic outcome than patients with PHASES scores <6 at discharge (58 [50%] vs. 90 [35%], P= 0.005) and follow-up (20 [17%] vs. 18 [6.9%], P= 0.002). After adjusting for age, Charlson Comorbidity Index score, nonsaccular aneurysm, andaneurysm size, PHASES score ≥6 remained a significant predictor of poor neurologic outcome at follow-up (odds ratio, 2.75; 95% confidence interval, 1.42-5.36, P= 0.003). In this retrospective analysis, a PHASES score ≥6 was associated with significantly greater proportions of poor outcome, suggesting that awareness of this threshold in PHASES scoring could be useful in risk stratification and UIA management.

Additional predictive value of optic nerve sheath diameter for neurological prognosis after cardiac arrest: a prospective cohort study

BackgroundThe goal is to estimate the additional value of ultrasonographic optic nerve sheath diameter (ONSD) measurement on days 1–3, on top of electroencephalography (EEG), pupillary light reflexes (PLR), and somatosensory evoked potentials (SSEP), for neurological outcome prediction of comatose cardiac arrest patients. We performed a prospective longitudinal cohort study in adult comatose patients after cardiac arrest. ONSD was measured on days 1–3 using ultrasound. Continuous EEG, PLR, and SSEP were acquired as standard care. Poor outcome was defined as cerebral performance categories 3–5 at 3–6 months. Logistic regression models were created for outcome prediction based on the established predictors with and without ONSD. Additional predictive value was assessed by increase in sensitivity for poor (at 100% specificity) and good outcome (at 90% specificity).ResultsWe included 100 patients, 54 with poor outcome. Mean ONSD did not differ significantly between patients with good and poor outcome. Sensitivity for predicting poor outcome increased by adding ONSD to EEG and SSEP from 25% to 41% in all patients and from 27% to 50% after exclusion of patients with non-neurological death.ConclusionsONSD on days 1–3 after cardiac arrest holds potential to add to neurological outcome prediction.Trialregistration: clinicaltrials.gov, NCT04084054. Registered 10 September 2019, https://www.clinicaltrials.gov/study/NCT04084054.

The role of intracranial pressure variability as a predictor of intracranial hypertension and mortality in critically ill patients.

Intracranial pressure (ICP) monitoring is a widely utilized and essential tool for tracking neurosurgical patients, but there are limitations to the use of a solely ICP-based paradigm for guiding management. It has been suggested that ICP variability (ICPV), in addition to mean ICP, may be a useful predictor of neurological outcomes, as it represents an indirect measure of intact cerebral pressure autoregulation. However, the current literature regarding the applicability of ICPV shows conflicting associations between ICPV and mortality. Thus, the authors aimed to investigate the effect of ICPV on intracranial hypertensive episodes and mortality using the eICU Collaborative Research Database version 2.0. The authors extracted from the eICU database 1,815,676 ICP readings from 868 patients with neurosurgical conditions. ICPV was computed using two methods: the rolling standard deviation (RSD) and the absolute deviation from the rolling mean (DRM). An episode of intracranial hypertension was defined as at least 25 minutes of ICP > 22 mm Hg in any 30-minute window. The effects of mean ICPV on intracranial hypertension and mortality were computed using multivariate logistic regression. A recurrent neural network with long short-term memory was used for time-series predictions of ICP and ICPV to prognosticate future episodes of intracranial hypertension. A higher mean ICPV was significantly associated with intracranial hypertension using both ICPV definitions (RSD: aOR 2.82, 95% CI 2.07-3.90, p < 0.001; DRM: aOR 3.93, 95% CI 2.77-5.69, p < 0.001). ICPV was significantly associated with mortality in patients with intracranial hypertension (RSD: aOR 1.28, 95% CI 1.04-1.61, p = 0.026, DRM: aOR 1.39, 95% CI 1.10-1.79, p = 0.007). In the machine learning models, both definitions of ICPV achieved similarly good results, with the best F1 score of 0.685 ± 0.026 and an area under the curve of 0.980 ± 0.003 achieved with the DRM definition over 20 minutes. ICPV may be useful as an adjunct for the prognostication of intracranial hypertensive episodes and mortality in neurosurgical critical care as part of neuromonitoring. Further research on predicting future intracranial hypertensive episodes with ICPV may help clinicians react expediently to ICP changes in patients.

An innovative MedIcaL dEcision Support tool for neurological ouTcome predictiOn from post-resuscitatioN Electrocardiograms (MILESTONE)

Abstract Background The prediction of poor neurological outcome after Out-of-Hospital Cardiac Arrest (OHCA) represents a major challenge in post-resuscitation care. This is currently based on a complex multiparametric prognostication approach and the existing decision support tools are characterized by unsatisfactory performance. Purpose The aim of the present study is to develop a machine learning (ML) tool for clinical decision support in the prediction of neurological outcome in patients who have experienced an OHCA. We present an innovative MedIcaL dEcision Support tool for neurological ouTcome predictiOn from post-resuscitatioN Electrocardiograms (MILESTONE), which can be used in a post-resuscitation setting. Methods MILESTONE uses an ECG image as an input from which it extracts features by computer vision techniques. Those features, used to feed the ML model for the prediction of the neurological outcome, were retrieved from a dataset of 1341 ECGs collected from a Utstein-style OHCA registry: 431 post-ROSC ECGs of patients with poor neurological outcome (defined according to the Cerebral Performance Category &amp;gt; 2) at discharge (class 1); 568 post-ROSC ECGs of patients with good neurological outcome (CPC≤2) and 342 ECGs of healthy subjects (class 0). Image features were extracted by several computer vision algorithms derived from the scale-invariant feature transform (SIFT) method. The extracted features, patient’s age and gender were used to train an XGBoost classifier. Nested cross-validation was applied to optimize the model’s parameters and to test its generalization capability. Class weightage technique was introduced to make our classifier more prone to detect positive cases. Model’s performance was evaluated by the balanced accuracy, the Area Under the Curve of the Receiver Operating Characteristic curve (AUC-ROC), and the F1-score in both the validation and the test sets. Results Our model achieved an AUC-ROC and F1-score of 88.5±4.1% and 78.2±7.3% respectively in the hold-out set (Figure). MILESTONE reached a balanced accuracy of over 80% as a proof of the robustness of the results and the high discrimination capability for both classes, although it has an intended bias towards the identification of patients with worse outcomes. In terms of explainability, MILESTONE has the potential to correlate machine-readable ECG features with more well-known macro features used in clinical practice such as QT intervals, peak shapes, etc. Conclusions We present the first use of computer vision-based ECG features able to predict poor neurological outcome in patients resuscitated from OHCA. Poor neurological outcome represents a major challenge in post-resuscitation care and this innovative and flexible tool showed an extremely promising performance. Moreover, this tool can be re-trained either for different pathologies or on any time length of ECG recording thus continuously improving its performance.

Electroencephalography Prediction of Neurological Outcomes After Hypoxic-Ischemic Brain Injury: A Systematic Review and Meta-Analysis.

Background. Predicting neurological outcomes after hypoxic-ischemic brain injury (HIBI) is difficult. Objective. Electroencephalography (EEG) can identify acute and subacute brain abnormalities after hypoxic brain injury and predict HIBI recovery. We examined EEG's ability to predict neurologic outcomes following HIBI. Method. A PRISMA-compliant search was conducted in the Medline, Embase, Cochrane, and Central databases until January 2023. EEG-predicted neurological outcomes in HIBI patients were selected from relevant perspective and retrospective cohort studies. RevMan did meta-analysis, while QDAS2 assessed research quality. Results. Eleven studies with 3761 HIBI patients met the inclusion and exclusion criteria. We aggregated study-level estimates of sensitivity and specificity for EEG patterns determined a priori using random effect bivariate and univariate meta-analysis when appropriate. Positive indicators and anatomical area heterogeneity impacted prognosis accuracy. Funnel plots analyzed publication bias. Significant heterogeneity of greater than 80% was among the included studies with P < 0.001. The area under the curve was 0.94, the threshold effect was P < 0.001, and the sensitivity and specificity, with 95% confidence intervals, were 0.91 (0.84-0.99) and 0.86 (0.75-0.97). EEG detects status epilepticus and burst suppression with good sensitivity, specificity, and little probability of false-negative impairment result attribution. Study quality varied by domain, but patient flow and timing were well conducted in all. Conclusion. EEG can predict the outcome of HIBI with good prognostic accuracy, but more standardized cross-study protocols and descriptions of EEG patterns are needed to better evaluate its prognostic use for patients with HIBI.

Relationship between Kidney Dysfunction, Stroke Severity, and Outcomes in a Nigerian Tertiary Hospital: A Prospective Study.

Stroke is a common neurologic disease associated with fatal outcomes. Kidney dysfunction may be an important predictor of stroke severity and outcome. To determine the relationship between kidney dysfunction at admission and stroke severity and 30-day outcome. This was a prospective study that involved 150 stroke patients. Stroke severity at admission was assessed using the National Institutes of Health Stroke Scale (NIHSS). Renal dysfunction was assessed by the presence of albuminuria and or reduced glomerular filtration rate (GFR) at admission. Neurological outcome was assessed using mortality, modified Rankin Scale (mRS), and Glasgow Outcome Scale (GCS). The mean age of the study participants was 61.0 ± 13.2 years. Renal dysfunction was present in 66% of the participants while the case fatality rate of stroke was 26%. Poor neurological outcome at 30 days was found in 44.1% of survivors. Those with albuminuria had lower GCS (P = 0.041), lower GFR (P = 0.004), higher mRS score on day 14 (P = 0.041) and day 30 (P = 0.032), and higher NIHSS score (P = 0.034). Independent predictors of 30-day mortality were albuminuria (Adjusted Odd Ratio (AOR) 3.60, 95%CI: 1.07-12.17) and increasing NIHSS score (AOR = 1.15, 95%CI: 1.04-1.28). Lower GCS (P < 0.001), elevated white blood cells (P = 0.003), serum creatinine (P = 0.048), and NIHSS score (P < 0.001) were associated with poor neurological outcome. NIHSS score was the only significant predictor of neurologic outcome (AOR: 1.25; CI: 1.11-1.41; P ≤ 0.001). Kidney dysfunction was associated with stroke severity and mortality. However, it was not an independent predictor of neurological outcome.

189 Role of Total Spectral Power in Prediction of Neurological Outcome After Cardiac Arrest

189 Role of Total Spectral Power in Prediction of Neurological Outcome After Cardiac Arrest

Quantitative analysis of early apparent diffusion coefficient values from MRIs for predicting neurological prognosis in survivors of out-of-hospital cardiac arrest: an observational study

BackgroundThis study aimed to quantitatively analyse ultra-early brain diffusion-weighted magnetic resonance imaging (DW-MRI) findings to determine the apparent diffusion coefficient (ADC) threshold associated with neurological outcomes in comatose survivors of out-of-hospital cardiac arrest (OHCA).MethodsThis retrospective study included adult survivors of comatose OHCA who underwent DW-MRI imaging scans using a 3-T MRI scanner within 6 h of the return of spontaneous circulation (ROSC). We investigated the association between neurological outcomes and ADC values obtained through voxel-based analysis on DW-MRI. Additionally, we constructed multivariable logistic regression models with pupillary light reflex (PLR), serum neuron-specific enolase (NSE), and ADC values as independent variables to predict poor neurological outcomes. The primary outcome was poor neurological outcome 6 months after ROSC, determined by the Cerebral Performance Category 3–5.ResultsOverall, 131 patients (26% female) were analysed, of whom 74 (57%) showed poor neurological outcomes. The group with a poor neurological outcome had lower mean whole brain ADC values (739.1 vs. 787.1 × 10–6 mm/s) and higher percentages of voxels with ADC below threshold in all ranges (250–1150) (all P < 0.001). The mean whole brain ADC values (area under the receiver operating characteristic curve [AUC] 0.83) and the percentage of voxels with ADC below 600 (AUC 0.81) had the highest sensitivity of 51% (95% confidence interval [CI] 39.4–63.1; cut-off value ≤ 739.2 × 10−6 mm2/s and > 17.2%, respectively) when the false positive rate (FPR) was 0%. In the multivariable model, which also included PLR, NSE, and mean whole brain ADC values, poor neurological outcome was predicted with the highest accuracy (AUC 0.91; 51% sensitivity). This model showed more accurate prediction and sensitivity at an FPR of 0% than did the combination of PLR and NSE (AUC 0.86; 30% sensitivity; P = 0.03).ConclusionsIn this cohort study, early voxel-based quantitative ADC analysis after ROSC was associated with poor neurological outcomes 6 months after cardiac arrest. The mean whole brain ADC value demonstrated the highest sensitivity when the FPR was 0%, and including it in the multivariable model improved the prediction of poor neurological outcomes.

Predictors of neurologic outcomes and mortality in physically abused and unintentionally injured children: a retrospective observation study

ObjectivesThis study aimed to identify the predictors of neurologic outcomes and mortality in physically abused and unintentionally injured children admitted to intensive care units (ICUs).MethodsAll maltreated children were admitted to pediatric, neurosurgical, and trauma ICUs between 2001 and 2019. Clinical factors, including age, sex, season of admission, identifying settings, injury severity score, etiologies, length of stay in the ICU, neurologic outcomes, and mortality, were analyzed and compared between the physically abused and unintentionally injured groups. Neurologic assessments were conducted using the Pediatric Cerebral Performance Category scale. The study was approved by the Institutional Review Board of Chang Gung Memorial Hospital and the Ethics Committee waived the requirement for informed consent because of the anonymized nature of the data.ResultsA total of 2481 children were investigated; of them, there were 480 (19.3%) victims admitted to the ICUs, including 156 physically abused and 324 unintentionally injured. Age, history of prematurity, clinical outcomes, head injury, neurosurgical interventions, clinical manifestations, brain computed tomography findings, and laboratory findings significantly differed between them (all p < 0.05). Traumatic brain injury was the major etiology for admission to the ICU. The incidence of abusive head trauma was 87.1% among the physically abused group. Only 46 (29.4%) and 268 (82.7%) cases achieved favorable neurologic outcomes in the physically abused and unintentionally injured groups, respectively. Shock within 24 h, spontaneous hypothermia (body temperature, < 35 °C), and post-traumatic seizure were strongly associated with poor neurologic outcomes and mortality in both groups.ConclusionsInitial presentation with shock, spontaneous hypothermia at ICU admission, and post-traumatic seizure were associated with poor neurologic outcomes and mortality in physically abused and unintentionally injured children.

Whether serum albumin/leukocyte ratio combined with Go-FAR score more accurately predicts the neurological outcome of patients who suffered cardiac arrest

Objective: To investigate whether serum albumin/leukocyte ratio combined with good outcome score after resuscitation (GO-FAR score) can improve the prediction of neurological outcomes in patients with cardiac arrest, so that clinical decisions can be made earlier and futile resuscitation can be avoided. Methods:The data of 72 patients with cardiac arrest rescued 2020.01.01-2022.04.30 in the Seventh Affiliated Hospital of Sun Yat-sen University were collected, and the GO-FAR score and albumin/leukocyte ratio of all patients were calculated. The main research outcome was the neurological outcome within one month after cardiac arrest. The brain function performance score (CPC score) was used for assessing neurological outcomes, It was divided into two groups:a good prognosis group (CPC score 1-2) and a poor prognosis group (CPC score 3-5). Multivariate Logistic analysis and ROC curve analysis were performed on the data of the two groups, and conclusions were drawn. Result:Univariate and multivariate analysis found that the albumin/leukocyte ratio and GO-FAR score in the poor prognosis group were lower than those in the good prognosis group, and the difference between the two groups was statistically significant (P &lt; 0.05).The results of ROC curve analysis found that the area under the curve of ALB/WBC, GO-FAR score, and ALB/WBC + GO-FAR score were: 0.782 (95% CI: 0.662 to 0.903), 0.677 (95% CI: 0.493 to 0.862), 0.841 (95% CI: 746-0.936), P &lt; 0.05, and the difference was statistically significant. Malignant tumor, shock rhythm, albumin, and leukocytes were all influencing factors for functional outcomes in patients with cardiac arrest. Conclusion:The combination of GO-FAR score and albumin/leukocyte ratio can better predict neurological outcomes in patients with cardiac arrest, but still cannot make instructions to stop resuscitation. More research is needed to confirm.

Confounders for prognostic accuracy of neuron-specific enolase after cardiac arrest: A retrospective cohort study

AimTo evaluate neuron-specific enolase (NSE) thresholds for prediction of neurological outcome after cardiac arrest and to analyze the influence of hemolysis and confounders. MethodsRetrospective analysis from a cardiac arrest registry. Determination of NSE serum concentration and hemolysis-index (h-index) 48–96 hours after cardiac arrest. Evaluation of neurological outcome using the Cerebral Performance Category score (CPC) at hospital discharge. Separate analyses considering CPC 1–3 and CPC 1–2 as good neurological outcome. Analysis of specificity and sensitivity for poor and good neurological outcome prediction with and without exclusion of hemolytic samples (h-index larger than 50). ResultsAmong 356 survivors three days after cardiac arrest, hemolysis was detected in 28 samples (7.9%). At a threshold of 60 µg/L, NSE predicted poor neurological outcome (CPC 4–5) in all samples with a specificity of 92% (86–95%) and sensitivity of 73% (66–79%). In non-hemolytic samples, specificity was 94% (89–97%) and sensitivity 70% (62–76%). At a threshold of 100 µg/L, specificity was 98% (95–100%, all samples) and 99% (95–100%, non-hemolytic samples), and sensitivity 58% (51–65%) and 55% (47–63%), respectively. Possible confounders for elevated NSE in patients with good neurological outcome were ECMO, malignancies, blood transfusions and acute brain diseases. Nine patients with NSE below 17 µg/L had CPC 5, all had plausible death causes other than hypoxic-ischemic encephalopathy. ConclusionsNSE concentrations higher than 100 µg/L predicted poor neurological outcome with high specificity. An NSE less than 17 µg/L indicated absence of severe hypoxic-ischemic encephalopathy. Hemolysis and other confounders need to be considered. Institutional protocol numberThe local ethics committee (board name: Ethikkommission der Charité) approved this study by the number: EA2/066/23, approval date: 28th June 2023, study title “‘ROSC’ – Resuscitation Outcome Study.”