Early Prediction Of Neurological Outcome Research Articles

External validation of the PROLOGUE score to predict neurological outcome in adult patients after cardiac arrest: a prospective cohort study

BackgroundThe PROLOGUE score (PROgnostication using LOGistic regression model for Unselected adult cardiac arrest patients in the Early stages) is a novel prognostic model for the prediction of neurological outcome after cardiac arrest, which showed exceptional performance in the internal validation. The aim of this study is to validate the PROLOGUE score in an independent cohort of unselected adult cardiac arrest patients and to compare it to the thoroughly validated Out-of-Hospital Cardiac Arrest (OHCA) and Cardiac Arrest Hospital Prognosis (CAHP) scores.MethodsThis study included consecutive adult cardiac arrest patients admitted to the intensive care unit (ICU) of a Swiss tertiary teaching hospital between October 2012 and July 2022. The primary endpoint was poor neurological outcome at hospital discharge, defined as a Cerebral Performance Category (CPC) score of 3 to 5 including death.ResultsOf 687 patients included in the analysis, 321 (46.7%) survived to hospital discharge with good neurological outcome, 68 (9.9%) survived with poor neurological outcome and 298 (43.4%) died. The PROLOGUE score showed an area under the receiver operating characteristic curve (AUROC) of 0.83 (95% CI 0.80 to 0.86) and good calibration for the prediction of the primary outcome. The OHCA and CAHP score showed similar performance (AUROC 0.83 and 0.84 respectively), the differences between the three scores were not significant (p = 0.495). In a subgroup analysis, the PROLOGUE score performed equally in out-of-hospital and in-hospital cardiac arrest patients whereas the OHCA and CAHP score performed significantly better in OHCA patients.ConclusionThe PROLOGUE score showed good prognostic accuracy for the early prediction of neurological outcome in adult cardiac arrest survivors in our cohort and might support early goals-of-care discussions in the ICU.Trial registration Not applicable.

Transcranial Doppler as an early predictor of neurological outcome in mild and moderate traumatic brain injury: An observational study

Background: Traumatic brain injury (TBI) is a major cause of disability and mortality globaly. The transcranial Doppler (TCD) method may show low diastolic blood flow velocity (FVd) and high pulsatility index (PI) measurements brought on by high vascular bed resistance. This study aimed to assess the usefulness of the TCD-PI for the early detection of secondary neurological deterioration (SND) in mild and moderate TBI. Materials and Methods: This prospective study was carried out on 105 mild and moderate TBI patients, who had TCD measurements within 12 h of the initial trauma, and initial computerized tomography (CT) showed mild lesion or no detected abnormality. Results: Primary end point was assessed (SND) within 1st week post trauma. Of the 105 patients with mild and moderate TBI, 29 (27.6%) showed SND. We evaluated the value of our intervention (TCD) to predict SND after mild and moderate TBI in 1st week. PI could predict SND at cutoff 1.21 with good sensitivity of 96.5% and specificity of 94.7%, area under curve (AUC) value of 0.98, negative predictive value (NPV) of 98.6%, and positive predictive value (PPV) of 87.5%. To amplify our finding, we measured FVd, and at 25 cm/s it showed good sensitivity 86.2% and specificity 89.5% when AUC 0.93, NPV 94.4%, and PPV 75.8%. Conclusion: TCD on admission may provide a valuable tool of early prediction of neurological outcome for mild and moderate TBI patients. Closing the gap in poor prediction of commonly used evaluation by CT especially with mild lesion.

Prognostic value of the myeloperoxidase index for early prediction of neurologic outcome in acute carbon monoxide poisoning.

ObjectiveCarbon monoxide (CO) activates intravascular neutrophils through platelet-neutrophil aggregates, which cause neutrophil degranulation. This process causes the release of myeloperoxidase (MPO), proteases, and reactive oxygen species. The MPO index (MPXI) is a newly reported inflammatory marker that reflects the MPO level within neutrophils. The MPXI in conditions associated with neutrophil activation depends on the net effect of azurophil degranulation. This study aimed to determine whether the MPXI can predict neurocognitive prognosis 1 month after acute CO poisoning.MethodsWe included patients aged ≥16 years with acute CO poisoning from a cohort at a single tertiary academic hospital in Wonju, Korea, between January 2010 and May 2021. Data from 699 patients were analyzed. The neurocognitive outcome was assessed using Global Deterioration Scale scores and classified as favorable (score, 1–3 points) or poor (score, 4–7 points). The MPXI was determined within 1 hour of arrival to the emergency department.ResultsAmong the 699 patients, 52 (7.4%) showed poor outcomes. The median MPXI of the patients in the poor outcome group was higher than that of the favorable outcome group (0.85 vs. 0.2, P=0.189). However, a significant difference was not found between the favorable and poor outcome groups, and MPXI was not a significant variable in multivariate logistic regression.ConclusionThe MPXI evaluated in the emergency department did not differ based on neurocognitive outcome at 1 month after acute CO poisoning.

Abstract 10100: Early Prediction of Neurological Outcome at 30 Days After Return of Spontaneous Circulation From Out-of-Hospital Cardiac Arrest

Aim: To develop and validate a model for early prediction of neurological outcomes in non-traumatic out-hospital cardiac arrest (OHCA) patients. Methods: We analyzed the data of adult non-traumatic cardiac arrest patients who experienced return of spontaneous circulation (ROSC) and were admitted to the intensive care unit between January 2013 and December 2017 from the database of a multicenter registry. We allocated 1329 patients who were admitted from 2013 to 2015 to the derivation set and 1025 patients admitted from 2016 to 2017 to the validation set. The primary outcome was the dichotomized Cerebral Performance Category at 30 days. We developed 2 models: model 1 including variables except for laboratory data and model 2 including all variables with laboratory data immediately available after ROSC. Logistic regression with least absolute shrinkage and selection operator regularization was used for model development. The C-statistics for discrimination, the prognostic ability, and calibration of the prediction model were assessed in the validation set. The reclassification of model 2 compared to model 1 was also evaluated by continuous net reclassification index (NRI). Results: The C-statistics [95% confidence intervals] of model 2 and 1 in validation set was 0.940 [0.921-0.959] and 0.935 [0.914-0.957], respectively (Figure 1). The calibration plot showed that both models were well-calibrated to observed neurological outcomes (Figure 2). The model 2 reclassified patients better than the model 1 (NRI: 0.663, p < 0.001). A web-based calculator based on these models was developed that allows clinicians to input the predictor variables needed for the probability of good or poor neurological outcomes (https://pcas-prediction.shinyapps.io/pcas_lasso/). Conclusion: The prediction tool including detailed in-hospital information showed good performance to predict neurological outcomes at 30 days in patients with ROSC after OHCA.

A practical risk score for early prediction of neurological outcome after out-of-hospital cardiac arrest: MIRACLE2.

The purpose of this study was to develop a practical risk score to predict poor neurological outcome after out-of-hospital cardiac arrest (OOHCA) for use on arrival to a Heart Attack Centre. From May 2012 to December 2017, 1055 patients had OOHCA in our region, of whom 373 patients were included in the King's Out of Hospital Cardiac Arrest Registry (KOCAR). We performed prediction modelling with multivariable logistic regression to identify predictors of the primary outcome to derive a risk score. This was externally validated in two independent cohorts comprising 473 patients. The primary endpoint was poor neurological outcome at 6-month follow-up (Cerebral Performance Category 3-5). Seven independent predictors of outcome were identified: missed (unwitnessed) arrest, initial non-shockable rhythm, non-reactivity of pupils, age (60-80 years-1 point; >80 years-3 points), changing intra-arrest rhythms, low pH <7.20, and epinephrine administration (2 points). The MIRACLE2 score had an area under the curve (AUC) of 0.90 in the development and 0.84/0.91 in the validation cohorts. Three risk groups were defined-low risk (MIRACLE2 ≤2-5.6% risk of poor outcome); intermediate risk (MIRACLE2 of 3-4-55.4% of poor outcome); and high risk (MIRACLE2 ≥5-92.3% risk of poor outcome). The MIRACLE2 score had superior discrimination than the OHCA [median AUC 0.83 (0.818-0.840); P < 0.001] and Cardiac Arrest Hospital Prognosis models [median AUC 0.87 (0.860-0.870; P = 0.001] and equivalent performance with the Target Temperature Management score [median AUC 0.88 (0.876-0.887); P = 0.092]. The MIRACLE2 is a practical risk score for early accurate prediction of poor neurological outcome after OOHCA, which has been developed for simplicity of use on admission.

Proteomics-Enriched Prediction Model for Poor Neurologic Outcome in Cardiac Arrest Survivors.

Neurologic outcome prediction in out-of-hospital cardiac arrest survivors is highly limited due to the lack of consistent predictors of clinically relevant brain damage. The present study aimed to identify novel biomarkers of neurologic recovery to improve early prediction of neurologic outcome. Prospective, single-center study, SETTING:: University-affiliated tertiary care center. We prospectively enrolled 96 out-of-hospital cardiac arrest survivors into our study. None. Neurologic outcome was assessed by the Cerebral Performance Categories score. To identify plasma biomarkers for poor neurologic outcome (Cerebral Performance Categories score ≥ 3), we performed a three-step proteomics strategy of preselection by shotgun analyses, crosschecking in brain tissue samples, and verification by targeted proteomic analyses using a multistep statistical modeling approach. Sixty-three patients (66%) had a poor neurologic outcome. Out of a total of 299 proteins, we identified α-enolase, 14-3-3 protein ζ/δ, cofilin-1, and heat shock cognate 71 kDa protein as novel biomarkers for poor neurologic outcome. The implementation of these biomarkers into a clinical multimarker model, consisting of previously identified covariates associated to outcome, resulted in a significant improvement of neurologic outcome prediction (C-index, 0.70; explained variation, 11.9%; p for added value, 0.019). This study identified four novel biomarkers for the prediction of poor neurologic outcome in out-of-hospital cardiac arrest survivors. The implementation of α-enolase, 14-3-3 protein ζ/δ, cofilin-1, and heat shock cognate 71 kDa protein into a multimarker predictive model along with previously identified risk factors significantly improved neurologic outcome prediction. Each of the proteomically identified biomarkers did not only outperform current risk stratification models but may also reflect important pathophysiologic pathways undergoing during cerebral ischemia.

Derivation and Validation of the SWAP Score for Very Early Prediction of Neurologic Outcome in Patients With Out-of-Hospital Cardiac Arrest

For patients with out-of-hospital cardiac arrest who receive cardiopulmonary resuscitation in an emergency department (ED), the early evaluation of their neurologic prognosis is essential for emergency physicians. The aim of this study is to establish a simple and useful assessment tool for rapidly estimating the prognosis of patients with out-of-hospital cardiac arrest after their arrival at an ED. A total of 852 patients admitted from January 1, 2015, to June 30, 2017, were prospectively registered and enrolled in thederivation cohort. Multivariate logistic regression on this cohort identified 4 independent factors associated with unfavorable outcomes: initial nonshockable rhythm (odds ratio [OR] 3.40; 95% confidence interval [CI] 1.58 to 7.32), no witness of collapse (OR3.19; 95% CI 1.51 to 6.75), older than 60 years (OR 3.65; 95% CI 1.64 to 8.09), and pH less than or equal to 7.00 (OR 3.27; 95% CI 1.42 to 7.54). The shockable rhythm-witness-age-pH (SWAP) score was developed and 1 point was assigned to each predictor. For a SWAP score of 4, the specificity was 97.14% (95% CI 91.62% to 100%) for unfavorable outcomes in the derivation cohort. For validation, we retrospectively collected data for 859 patients with out-of-hospital cardiac arrest from January 1, 2012, to December 31, 2014. A SWAP score of 4 was 100% specific (95% CI 99.9% to 100%) for unfavorable outcomes in the validation cohort. The SWAP score is a simple and useful predictive model that may provide information for the very early estimation of prognosis for patients with out-of-hospital cardiac arrest. Further research is required to integrate ultrasonographic findings and validate the SWAP score's application in other populations.

MRI for early prediction of outcome in preterm infants: Which items?

Objectives Early prediction of neurologic outcome of preterm infants is challenging. MRI provides interesting insights. Usual MRI interpretation looking for lesions (hemorrhage, cystic lesions, infarction, or “qualitative abnormalities”) has good predictive value for severe motor disabilities. Conversely those standard items are poor predictors of later, cognitive impairments. For this purpose, measuring volume of brain structures and cerebral growth is promising. In a prospective cohort study, we assessed global and regional cerebral growth, compared to outcome. Methods Infants born before 30 gestation weeks underwent serial MRI (between 25 and 28 weeks of gestation, then every three weeks until term). Cerebrum, cerebellum, brainstem, fluid spaces were estimated through twenty-five 2D measurements. Outcome was assessed with Bayley scale at two years of age. Results Hundred and eight preterm infants were included and 266 MRI performed. Main qualitative abnormalities were low-grade IVH (22%), severe IVH (6%), severe white matter injuries (21%), Cerebellar injuries (19%). Brain/Bone biparietal diameter, which has previously been strongly correlated with global cerebral volume, was significantly lower, as cerebellum and brainstem measurements. Impairment of regional brain growth is correlated with 2 years outcome. Conclusion We need to further search for correlation with later outcome at five and eight years. Brain MRI is a promising tool for early prognosis, but standard interpretation might include volume and cerebral growth assessments.

T114. Predicting coma outcome using resting-state fMRI and machine learning

Introduction Early prediction of neurological outcome of post-anoxic comatose patients after cardiac arrest(CA) is challenging. Prognosis of comatose patient relies on multimodal testing: clinical examination, electrophysiological testing and structural neuroimaging (mainly diffusion MRI DWI). This multimodal prognostication is accurate for predicting poor outcome(i.e.death) but not sensitive for identifying patients with good outcome (i.e. consciousness recovery). Resting state functional MRI (rs-fMRI) is a powerful tool for mapping functional connectivity, especially in patients with low collaboration. Several studies showed that rs-fMRI can differentiate states of consciousness in chronically brain damaged patients. A recent study also showed that fMRI can detect early signs of consciousness in patient with acute traumatic brain injury. However, rs-fMRI has not been systematically assessed for the early prognositcation of post-anoxic comatose patient. Methods We assessed whole brain functional connectivity (FC) of 17 post-anoxic comatose patients early after CA using rs-fMRI. Nine patients recovered consciousness(good outcome) while eight died(poor outcome). We estimated FC for each patient following a standard procedure described by Leonardi and Richiardi et al. We statistically compared whole brain FC between good and poor outcome group, to assess which brain connections differed between them. Then, we trained a machine learning classifier(a Support Vector Machine classifier, SVM) using a Leave-One-Out Cross-Validation method, to automatically predict coma outcome (good/poor) based on whole-brain FC of comatose patients. Finally, we compared this outcome-prognostication based on fMRI to those using standard structural DWI. Results Good and poor coma outcome groups were similar in terms of demographics, except for time to ROSC. Good outcome group showed significant increase in whole-brain FC between most cortical brain regions, with the strongest changes occuring within and between occipital and parietal, temporal and frontal regions. Using whole-brain FC and a SVM classifier to predict coma outcome yielded to an overall prediction accuracy of 94.4% (AUC 0.94). Interestingly, automatic outcome prognostication using functional neuroimaging achieved better results that state-of the-art structural neuroimaging methods like DWI (accuracy 70.6%). Conclusion We used rs-fMRI to predict coma outcome in a cohort of post-anoxic comatose patients early after CA. We deliberately chose to include only patients with indeterminate prognosis after standard multimodal testing, in order to assess the contribution of rs-fMRI in the early prognostication of coma outcome. We found that automatic prediction based on fMRI yielded much better results than current diffusion neuroimaging methods, notably for identifying patients who recovered consciousness.

Comparison of brain computed tomography and diffusion-weighted magnetic resonance imaging to predict early neurologic outcome before target temperature management comatose cardiac arrest survivors

AimWe previously reported that diffusion-weighted magnetic resonance imaging (DW-MRI) could be used to predict neurologic outcomes before targeted temperature management (TTM) after return of spontaneous circulation (ROSC) from cardiac arrest (CA). We compared the efficacy of brain computed tomography (CT) and DW-MRI to predict neurologic outcome before TTM in comatose cardiac arrest survivors. MethodsWe performed a retrospective study of CA patients treated with TTM. The brain CT and DW-MRI were both obtained before TTM. We analysed the grey matter to white matter ratio (GWR) on the brain CT and the presence of high signal intensity on DW-MRI, alone or in combination, to predict poor neurologic outcome (CPC 3–5). ResultsOf 47 comatose CA patients treated with TTM, 39 patients with brain CT and DW-MRI data were included. Median time from the ROSC to the brain CT and DW-MRI was 90min (52–150) and 175min (118–240), respectively. There was no significant difference in predicting poor neurologic outcome between average GWR (area under the curve [AUC] 0.891, sensitivity/specificity 78.8%/100%) and DW-MRI (AUC 0.894, sensitivity/specificity 75.8%/100%) (p=0.963). The combination of average GWR and DW-MRI (AUC 0.939, sensitivity/specificity 87.9%/100%) improved the prediction of poor neurologic outcome rather than each one alone and in other combinations. ConclusionOur preliminary finding suggests that DW-MRI is potentially useful for early prediction of neurologic outcome (i.e., before TTM) in CA patients. The combination of GWR on brain CT and that on DW-MRI, rather than on each modality alone, appears to improve the sensitivity for predicting neurologic outcome after ROSC from CA. Large prospective multicenter studies should be conducted to confirm these results.

Immature/total granulocyte ratio improves early prediction of neurological outcome after out-of-hospital cardiac arrest: the MyeloScore study.

BackgroundElevation of the immature/total granulocyte (I/T-G) ratio has been reported after out-of-hospital cardiac arrest (OHCA). Our purpose here was to evaluate the prognostic significance of the I/T-G ratio and to investigate whether the I/T-G ratio improves neurological outcome prediction after OHCA.MethodsThis single-center prospective cohort study included consecutive immunocompetent patients admitted to our intensive care unit over a 3-year period (2012–2014) after successfully resuscitated OHCA. The I/T-G ratio was determined in blood samples collected at admission.ResultsWe studied 204 patients (77 % male, median age, 58 [48–67] years), of whom 64 % had a suspected cardiac cause of OHCA, 62 % died in the unit, and 31.5 % survived with good cerebral function. Independent outcome predictors by multivariate analysis were age, first shockable rhythm, bystander-initiated resuscitation, and I/T-G ratio. Compared to the model computed without the I/T-G ratio, the model with the ratio performed significantly better [areas under the ROC curves (AUCs), 0.78 vs. 0.83, respectively; P = 0.04]. These items were used to develop the MyeloScore equation: ([0.47 × I/T-G ratio] + [0.023 × age in years]) − 1.26 if initial VF/VT − 1.1 if bystander-initiated CPR. The MyeloScore predicted neurological outcomes with similar accuracy to the previously reported OHCA score (0.83 and 0.85, respectively; P = 0.6). The ROC–AUC was 0.84, providing external validation of the MyeloScore.ConclusionsThe I/T-G ratio independently predicts neurological outcome after OHCA and, when added to other known risk factors, improves neurological outcome prediction. The clinical performance of the MyeloScore requires evaluation in a prospective study.

Regional cerebral oxygen saturation after cardiac arrest in 60 patients—A prospective outcome study

IntroductionNon-invasive near-infrared spectroscopy (NIRS) offers the possibility to determine regional cerebral oxygen saturation (rSO2) in patients with cardiac arrest. Limited data from recent studies indicate a potential for early prediction of neurological outcome. MethodsSixty cardiac arrest patients were prospectively enrolled, 22 in-hospital cardiac arrest (IHCA) and 38 out-of-hospital cardiac arrest (OHCA) patients respectively. NIRS of frontal brain was started after return of spontaneous circulation (ROSC) during admission to ICU and was continued until normothermia. Outcome was determined at ICU discharge by the Pittsburgh Cerebral Performance Category (CPC) and 6 months after cardiac arrest. ResultsA good outcome (CPC 1–2) was achieved in 23 (38%) patients, while 37 (62%) had a poor outcome (CPC 3–5). Patients with good outcome had significantly higher rSO2 levels (CPC 1–2: rSO2 68%; CPC 3–5: rSO2 58%; p<0.01). For good and poor outcome median rSO2 within the first 24h period was 66% and 59% respectively and for the following 16h period 68% and 59% (p<0.01). Outcome prediction by area of rSO2 below a critical threshold of rsO2=50% within the first 40h yielded 70% specificity and 86% sensitivity for poor outcome. ConclusionOn average, rSO2 within the first 40h after ROSC is significantly lower in patients with poor outcome, but rSO2 ranges largely overlap between outcome groups. Our data indicate limited potential for prediction of poor outcome by frontal brain rSO2 measurements.

The Relation between Neurologic Prognosis and Optic Nerve Sheath Diameter Measured in Initial Brain Computed Tomography of Cardiac Arrest and Hanging Patients

Background: Early prediction of neurologic outcome is important to patients treated with therapeutic hypothermia after hypoxic brain injury. Hypoxic brain injury patients may have poor neurologic prognosis due to increased intracranial pressure. Increased intracranial pressure can be detected by optic nerve sheath diameter (ONSD) measurement in computed tomography (CT) or ultrasound. In this study, we evaluate the relation between neurologic prognosis and optic nerve sheath diameter measured in brain CT of hypoxic brain injury patients. Methods: We analyzed the patient clinical data by retrospective chart review. We measured the ONSD in initial brain CT. We also measured and calculated the gray white matter ratio (GWR) in CT scan. We split the patients into two groups based on neurologic outcome, and clinical data, ONSD, and GWR were compared in the two groups. Results: Twenty-four patients were included in this study (age: 52.6 ± 18.3, 18 males). The mean ONSD of the poor neurologic outcome group was larger than that of the good neurologic outcome group (6.07 mm vs. 5.39 mm, p = 0.003). The GWR of the good neurologic outcome group was larger than that of the poor outcome group (1.09 vs. 1.28, p = 0.000). ONSD was a good predictor of neurologic outcome (area under curve: 0.848), and an ONSD cut off ≥ 5.575 mm had a sensitivity of 86.7% and a specificity of 77.8%. Conclusions: ONSD measured on the initial brain CT scan can predict the neurologic prognosis in cardiac arrest and hanging patients treated with therapeutic hypothermia.

Abstract 235: The Glasgow Motor Score Before Induction of Therapeutic Hypothermia Is an Independent Predictor of Good Outcome in Cardiac Arrest

Background: With the recent introduction of therapeutic hypothermia, the application of sedation becomes necessary in cardiac arrest patients. Therefore early prediction of neurologic outcome in these patients is challenging problem. Nevertheless neurologic examination including the Glasgow coma scale should be basis for decision making. So, we investigated the usefulness of the Glasgow motor score before induction of therapeutic hypothermia for outcome prediction in survivors of cardiac arrest treated with therapeutic hypothermia. Methods: Between March 2009 and July 2011, patients who successfully resuscitated from cardiac arrest and treated with mild therapeutic hypothermia were included in this study. Data were collected by local post-cardiac arrest care registry. Neurologic outcome was assessed with Cerebral Performance Category (CPC) at hospital discharge and good neurologic outcome was defined CPC score of 1 and 2. Results: Total 89 patients were treated with therapeutic hypothermia during study period. Among these patients, 39 were good neurologic outcome and 50 were poor neurologic outcome. The value for prediction of good outcome was as follows: sensitivity 53.8%, specificity 96.0%, PPV 91.3%, NPV 72.7% and AUC 0.749. Conclusions: The results of this study show that the Glasgow motor score &gt; 1 before induction of therapeutic hypothermia is an independent predictor of good outcome in patients treated with therapeutic hypothermia. Thus, the patients with the Glasgow motor score &gt; 1 soon after ROSC should be treated aggressively including therapeutic hypothermia.

Continuous electroencephalography monitoring for early prediction of neurological outcome in postanoxic patients after cardiac arrest

To evaluate the value of continuous electroencephalography in early prognostication in patients treated with hypothermia after cardiac arrest. Prospective cohort study. Medical intensive care unit. Sixty patients admitted to the intensive care unit for therapeutic hypothermia after cardiac arrest. None. In all patients, continuous electroencephalogram and daily somatosensory evoked potentials were recorded during the first 5 days of admission or until intensive care unit discharge. Neurological outcomes were based on each patient's best achieved Cerebral Performance Category score within 6 months. Twenty-seven of 56 patients (48%) achieved good neurological outcome (Cerebral Performance Category score 1-2).At 12 hrs after resuscitation, 43% of the patients with good neurological outcome showed continuous, diffuse slow electroencephalogram rhythms, whereas this was never observed in patients with poor outcome.The sensitivity for predicting poor neurological outcome of low-voltage and isoelectric electroencephalogram patterns 24 hrs after resuscitation was 40% (95% confidence interval 19%-64%) with a 100% specificity (confidence interval 86%-100%), whereas the sensitivity and specificity of absent somatosensory evoked potential responses during the first 24 hrs were 24% (confidence interval 10%-44%) and 100% (confidence interval: 87%-100%), respectively. The negative predictive value for poor outcome of low-voltage and isoelectric electroencephalogram patterns was 68% (confidence interval 50%-81%) compared to 55% (confidence interval 40%-60%) for bilateral somatosensory evoked potential absence, both with a positive predictive value of 100% (confidence interval 63%-100% and 59%-100% respectively). Burst-suppression patterns after 24 hrs were also associated with poor neurological outcome, but not inevitably so. In patients treated with hypothermia, electroencephalogram monitoring during the first 24 hrs after resuscitation can contribute to the prediction of both good and poor neurological outcome. Continuous patterns within 12 hrs predicted good outcome. Isoelectric or low-voltage electroencephalograms after 24 hrs predicted poor outcome with a sensitivity almost two times larger than bilateral absent somatosensory evoked potential responses.

Predictive Value of Early Long-Term Monitoring of Total Absolute Band Power (TABP) in Premature Infants Correlated to Neurologic Outcome at 24 Months of Age

Background: Continuous long-term multichannel EEG monitoring of premature infant is feasible and could be a useful tool for detection of pathological processes and an early prediction of neurologic outcome. Aim: To evaluate for correlations between tABP from day 1 to 3 in premature infants and their neurologic outcome at 24 months of age. Methods: Forty one premature infants, GA 24-31 wks, were included and monitored (NicoletOne monitor) continuously for 3 days from soon after birth. The infants were divided into group 1 (GA 24-28 wks) and group 2 (GA 28-31 wks). Eight EEG electrodes were applied. tABP of all bands were analyzed. Mental and motor development was assessed by Bayley Scales of Infant Development II (BSID II) and Peabody Developmental Motor Scales (PDMS) at 24 months of age. Using standard procedures, raw scores were converted to the age-normed Mental Development Index, Psychomotor Development Index and Total Motor Quotient. These index and quotient scores have a population mean of 100 and a standard deviation of 15. The test results were ranked in normal or abnormal neurologic outcome (normal: index ≥ 85; abnormal: index < 85). Results: In group1 there was a significant lower tABP day 1-3 in infants with poor neurologic outcome (index < 85) than in infants with normal outcome. The same was not seen in group 2. Conclusion: This study shows a good correlation between low tABP during the 3 first days of life and poor neurologic outcome at 24 months of age in premature infants with GA< 28 wks.

Early prediction of neurological outcome by term neurological examination and cranial ultrasound in very preterm infants

To assess the value of term neurological examination and cranial ultrasound in the early prediction of neurological outcome at 12 months corrected age in a cohort of very preterm infants. A cohort of 102 preterm infants born at <32 weeks gestation or with a birth weight of <1500 g were assessed using the Hammersmith Term Neurological Examination. They underwent cranial ultrasound examinations according to local guidelines. The Hammersmith Infant Neurological Examination was performed at 12 months corrected age. Scores for the term examinations were compared with scores derived from healthy infants born at term and with scores from low-risk preterm infants at term equivalent age. Term neurological scores and cranial ultrasound findings were compared in the prediction of 12-month neurological outcome. Seventy-eight (76.5%) preterm infants had suboptimal total neurological scores at term when compared to healthy infants born at term. However, most went on to have optimal neurological scores at 12 months corrected age. When our cohort was compared with low-risk preterm infants at term equivalent age only 14 (13.7%) scored outside the normal range. Neither system of scoring predicted neurological outcome at 12 months corrected age as reliably as cranial ultrasound (sensitivity 0.83, specificity 0.87). Neurological examination of preterm babies at term may be unreliable in the prediction of neurological outcome at 12 months corrected age. For early prediction of neurological outcome cranial ultrasound examination was found to be more reliable.

Early prediction of neurological outcome by term neurological examination and cranial ultrasound in very preterm infants. Acta Paediatrica 2009, Amess et al.

Early prediction of neurological outcome by term neurological examination and cranial ultrasound in very preterm infants. <i>Acta Paediatrica</i> 2009, Amess <i>et al</i>.

Early Prediction of Neurological Outcome after Cardiopulmonary Resuscitation: A Multimodal Approach Combining Neurobiochemical and Electrophysiological Investigations May Provide High Prognostic Certainty in Patients after Cardiac Arrest

A reliable and reproducible method for precisely predicting the neurological outcome of patients with hypoxic-ischemic encephalopathy after cardiac arrest is urgently needed in neurological intensive care units. We prospectively investigated the predictive power of serum concentrations of neuron-specific enolase (NSE) and protein S-100B (S-100B) measured on days 1, 2, 3 and 7 as well as somatosensory-evoked potentials (SEPs) recorded within 48 h and on day 7 after cardiopulmonary resuscitation (CPR) in 27 patients (14 females, 13 males; mean age 61.3 ± 17.3 years) with hypoxic-ischemic encephalopathy. During the first 7 days after CPR, median values of NSE and S-100B were increased in patients who remained unconscious after CPR compared to those patients who regained consciousness (significance up to ≤0.001). The best predictor of negative outcome was an NSE cutoff point ≧43 µg/l on day 2; this had a sensitivity of 90.9% and a specificity of 100%. Additional use of S-100B on day 2 did not increase sensitivity, but this could be markedly increased by combining NSE and S-100B on days 1, 3 and 7. SEPs showing bilateral loss of cortical responses identified patients who did not regain consciousness with a specificity of 100%.

Early Prediction of Neurologic Outcome After Perinatal Depression

Evaluation is presented of whether or not a detailed neuromotor examination at 3 months of age could predict later neurologic abnormalities among term infants with perinatal depression. In a prospective cohort, infants were neurologically evaluated at 3 and 12 months. Infants were scored from 0 to 5 according to a new neuromotor scoring system. The neuromotor score at 3 months (NMS-3) was compared with the NMS at 12 months (NMS-12). Seventy-four infants were enrolled in the study; nine were lost to follow-up, and five died before reaching 1 year. Sixty infants were examined (neurologic abnormalities = 52%, normal = 48% at 1 year). The NMS-3 correlated strongly with the NMS-12 and the results of the 12-month neurologic examination. All infants with a NMS-3 of 5 had neurologic abnormalities at 1 year. Infants with neonatal seizures had a significantly increased risk of developmental abnormalities at 1 year. Eighteen infants exhibited transient abnormalities. Using a simple scoring system, the results of the early neurologic examinations correlated strongly with outcome among term infants with perinatal depression. A subgroup of infants had transient abnormalities. These findings suggest that in term high-risk infants, the 1-year neurologic outcome can be predicted at 3 months of age using these parameters.