Daiquan Gao

Improved Neurological Outcome With Mild Hypothermia in Surviving Patients With Massive Cerebral Hemispheric Infarction

Background and Purpose— We conducted this randomized controlled trial to investigate the effects of therapeutic hypothermia on mortality and neurological outcome in patients with massive cerebral hemispheric infarction. Methods— Patients within 48 hours of symptom onset were randomized to either a hypothermia group or a control group. Patients in the hypothermia group were given standard medical treatment plus endovascular hypothermia with a target temperature of 33 or 34°C. Hypothermia was maintained for a minimum of 24 hours. Patients in the control group were given standard medical treatment only with a target temperature of normothermia. The primary end points were mortality and the modified Rankin Scale score at 6 months. Results— There were 16 patients in the hypothermia group and 17 patients in the control group. At 6 months, 8 patients had died in the hypothermia group versus 7 patients in the control group (P=0.732). The main cause of death was fatal herniation caused by a pronounced rise in intracranial pressure. Seven patients (43.8%) had a modified Rankin Scale of 1 to 3 in the hypothermia group versus 4 patients (23.5%) in the control group (P=0.282). Additionally, of the survivors, patients in the hypothermia group achieved better neurological outcomes compared with those in the control group (7/8, 87.5% versus 4/10, 40.0%; P=0.066; odds ratio=10.5; 95% confidence interval, 0.9–121.4). Conclusions— Mild hypothermia seems to not reduce mortality in patients with massive cerebral hemispheric infarction but may improve the neurological outcome in survivors. An adequately powered multicenter randomized controlled trial seems warranted. Clinical Trial Registration— URL: http://www.chictr.org.cn. Unique identifier: ChiCTR-TCS-12002680.

Poor outcome prediction by burst suppression ratio in adults with post-anoxic coma without hypothermia

Abstract Purpose: Burst suppression ratio (BSR) is a quantitative electroencephalography (qEEG) parameter. The purpose of our study was to compare the accuracy of BSR when compared to other EEG parameters in predicting poor outcomes in adults who sustained post-anoxic coma while not being subjected to therapeutic hypothermia. Methods: EEG was registered and recorded at least once within 7 days of post-anoxic coma onset. Electrodes were placed according to the international 10–20 system, using a 16-channel layout. Each EEG expert scored raw EEG using a grading scale adapted from Young and scored amplitude-integrated electroencephalography tracings, in addition to obtaining qEEG parameters defined as BSR with a defined threshold. Glasgow outcome scales of 1 and 2 at 3 months, determined by two blinded neurologists, were defined as poor outcome. Results: Sixty patients with Glasgow coma scale score of 8 or less after anoxic accident were included. The sensitivity (97·1%), specificity (73·3%), positive predictive value (82·5%), and negative prediction value (95·0%) of BSR in predicting poor outcome were higher than other EEG variables. BSR1 and BSR2 were reliable in predicting death (area under the curve > 0·8, P < 0·05), with the respective cutoff points being 39·8% and 61·6%. BSR1 was reliable in predicting poor outcome (area under the curve  =  0·820, P < 0·05) with a cutoff point of 23·9%. BSR1 was also an independent predictor of increased risk of death (odds ratio  =  1·042, 95% confidence intervals: 1·012–1·073, P  =  0·006). Discussion: BSR may be a better predictor in prognosticating poor outcomes in patients with post-anoxic coma who do not undergo therapeutic hypothermia when compared to other qEEG parameters.

Early Hypothermia for Refractory Status Epilepticus.

IntroductIon Currently, the recommended therapy to control refractory status epilepticus (RSE) is intravenous (IV) anesthetics, such as midazolam, propofol, barbiturates, and so on. However, 15%–26% of RSE cases still cannot be terminated. Three case series studies have demonstrated that the combination of IV anesthetics and moderate (30–31°C) or mild (31–35°C) hypothermia successfully terminated the seizures in RSE patients.[1,2] But the high rebound rate after rewarming, high mortality rate during hospitalization and severe neurological deficits were still unsatisfactory.[1,2] We hypothesized that starting hypothermia earlier, an hour after IV anesthetic, rather than a few days later, may get the best effect on the termination of RSE and has a better prognosis. The purpose of this research was to confirm the effect of the combination of early hypothermia and IV anesthetic on suppressing seizures and improving prognosis.

Electroencephalography reactivity for prognostication of post-anoxic coma after cardiopulmonary resuscitation: A comparison of quantitative analysis and visual analysis.

Electroencephalogram reactivity (EEG-R) is a positive predictive factor for assessing outcomes in comatose patients. Most studies assess the prognostic value of EEG-R utilizing visual analysis; however, this method is prone to subjectivity. We sought to categorize EEG-R with a quantitative approach. We retrospectively studied consecutive comatose patients who had an EEG-R recording performed 1-3 days after cardiopulmonary resuscitation (CPR) or during normothermia after therapeutic hypothermia. EEG-R was assessed via visual analysis and quantitative analysis separately. Clinical outcomes were followed-up at 3-month and dichotomized as recovery of awareness or no recovery of awareness. A total of 96 patients met the inclusion criteria, and 38 (40%) patients recovered awareness at 3-month followed-up. Of 27 patients with EEG-R measured with visual analysis, 22 patients recovered awareness; and of the 69 patients who did not demonstrated EEG-R, 16 patients recovered awareness. The sensitivity and specificity of visually measured EEG-R were 58% and 91%, respectively. The area under the receiver operating characteristic curve for the quantitative analysis was 0.92 (95% confidence interval, 0.87-0.97), with the best cut-off value of 0.10. EEG-R through quantitative analysis might be a good method in predicting the recovery of awareness in patients with post-anoxic coma after CPR.

Protocol-directed weaning from mechanical ventilation in neurological patients: a randomised controlled trial and subgroup analyses based on consciousness

Abstract Objectives: To assess whether a weaning protocol reduces the mechanical ventilation (MV) duration compared to physicians judgement-based weaning in neurological patients and to determine whether patient consciousness influences this reduction. Methods: A randomised controlled trial was conducted in a neurological intensive care unit (NCU) of a tertiary hospital; 144 patients requiring MV for more than 24 hours were randomly allocated to protocol-directed (intervention) (n = 71) or physician-directed (control) group (n = 73). Results: The intervention group displayed a significantly shorter median weaning time than the control group (2.00 vs 5.07 days, P < 0.05). The median MV duration tended to be shorter in the intervention group (10.8 vs 14.2 days, P = 0.106). The median length of NCU stay was 19.0 and 26.1 days in the intervention and control groups, respectively (P = 0.063). The median NCU cost was 9.26 × 104 and 12.24 × 104 ¥ in the intervention and control groups, respectively (P = 0.059). The unsuccessful weaning, ventilator-associated pneumonia (VAP) and mortality rates were similar between the groups. Among conscious patients, the median weaning time (2.00 vs 7.00 days, P < 0.05) and the median MV duration (8.8 vs 18.0 days, P = 0.017) were significantly reduced in the intervention group. Among unconscious patients, the intervention group displayed a reduced median weaning time (1.00 vs 3.10 days, P < 0.05), but not median MV duration (11.6 vs 11.1 days, P = 0.702), compared to the control group. Conclusion: Protocol-directed weaning reduces weaning time, MV duration, length of NCU stay and NCU cost in neurological patients, and these effects are more significant in conscious patients than in unconscious patients.

Predicting Outcome in Comatose Patients: The Role of EEG Reactivity to Quantifiable Electrical Stimuli

Objective. To test the value of quantifiable electrical stimuli as a reliable method to assess electroencephalogram reactivity (EEG-R) for the early prognostication of outcome in comatose patients. Methods. EEG was recorded in consecutive adults in coma after cardiopulmonary resuscitation (CPR) or stroke. EEG-R to standard electrical stimuli was tested. Each patient received a 3-month follow-up by the Glasgow-Pittsburgh cerebral performance categories (CPC) or modified Rankin scale (mRS) score. Results. Twenty-two patients met the inclusion criteria. In the CPR group, 6 of 7 patients with EEG-R had good outcomes (positive predictive value (PPV), 85.7%) and 4 of 5 patients without EEG-R had poor outcomes (negative predictive value (NPV), 80%). The sensitivity and specificity were 85.7% and 80%, respectively. In the stroke group, 6 of 7 patients with EEG-R had good outcomes (PPV, 85.7%); all of the 3 patients without EEG-R had poor outcomes (NPV, 100%). The sensitivity and specificity were 100% and 75%, respectively. Of all patients, the presence of EEG-R showed 92.3% sensitivity, 77.7% specificity, 85.7% PPV, and 87.5% NPV. Conclusion. EEG-R to quantifiable electrical stimuli might be a good positive predictive factor for the prognosis of outcome in comatose patients after CPR or stroke.

Module modified acute physiology and chronic health evaluation II: predicting the mortality of neuro-critical disease

Abstract Objectives: This study aimed to conduct and assess a module modified acute physiology and chronic health evaluation (MM-APACHE) II model, based on disease categories modified-acute physiology and chronic health evaluation (DCM-APACHE) II model, in predicting mortality more accurately in neuro-intensive care units (N-ICUs). Methods: In total, 1686 patients entered into this prospective study. Acute physiology and chronic health evaluation (APACHE) II scores of all patients on admission and worst 24-, 48-, 72-hour scores were obtained. Neurological diagnosis on admission was classified into five categories: cerebral infarction, intracranial hemorrhage, neurological infection, spinal neuromuscular (SNM) disease, and other neurological diseases. The APACHE II scores of cerebral infarction, intracranial hemorrhage, and neurological infection patients were used for building the MM-APACHE II model. Results: There were 1386 cases for cerebral infarction disease, intracranial hemorrhage disease, and neurological infection disease. The logistic linear regression showed that 72-hour APACHE II score (Wals  =  173·04, P < 0·001) and disease classification (Wals  =  12·51, P  =  0·02) were of importance in forecasting hospital mortality. Module modified acute physiology and chronic health evaluation II model, built on the variables of the 72-hour APACHE II score and disease category, had good discrimination (area under the receiver operating characteristic curve (AU-ROC  =  0·830)) and calibration (χ2  =  12·518, P  =  0·20), and was better than the Knaus APACHE II model (AU-ROC  =  0·778). Discussion: The APACHE II severity of disease classification system cannot provide accurate prognosis for all kinds of the diseases. A MM-APACHE II model can accurately predict hospital mortality for cerebral infarction, intracranial hemorrhage, and neurologic infection patients in N-ICU.

RSE prediction by EEG patterns in adult GCSE patients

BACKGROUND Electroencephalogram (EEG) can predict mortality in status epilepticus (SE) patients. However, we consider that the prediction for refractory status epilepticus (RSE) after SE initial treatment is more significant than long-term prognosis of SE. The objective of this study is to detect some predictive EEG patterns for RSE. METHODS Pooled data derived from two randomized controlled trials (RCTs) were prospectively analyzed in adult generalized convulsive status epilepticus (GCSE) patients. RESULTS Etiology, GCSE duration and EEG patterns are three factors which were statistically different between non-RSE and RSE groups. However, when we introduced these factors into multivariable logistic regression model, only EEG pattern was an independent risk factor for RSE prediction. Comparing with rhythmic fast activities background (RFAB) pattern, there were positive correlations between interictal epileptiform discharges (IEDs), periodic epileptic discharges/subtle status epilepticus (PEDs/subtle SE) patterns and RSE incidence respectively. CONCLUSIONS There was an increased risk of RSE incidence accompanied with IEDs and PEDs/subtle SE patterns appearance. Clinicians should adjust anti-epileptic strategies with the aid of these EEG patterns in order to reduce RSE incidence.

Study of Simplified Coma Scales: Acute Stroke Patients with Tracheal Intubation

Background: Whether the Glasgow Coma Scale (GCS) can assess intubated patients is still a topic of controversy. We compared the test performance of the GCS motor component (GCS-M)/Simplified Motor Score (SMS) to the total of the GCS in predicting the outcomes of intubated acute severe cerebral vascular disease patients. Methods: A retrospective analysis of prospectively collected observational data was performed. Between January 2012 and October 2015, 106 consecutive acute severe cerebral vascular disease patients with intubation were included in the study. GCS, GCS-M, GCS eye-opening component, and SMS were documented on admission and at 24, 48, and 72 h after admission to Neurointensive Care Unit (NCU). Outcomes were death and unfavorable prognosis (modified Rankin Scale: 5–6) at NCU discharge. The receiver operating characteristic (ROC) curve was obtained to determine the prognostic performance and best cutoff value for each scoring system. Comparison of the area under the ROC curves (AUCs) was performed using the Z-test. Results: Of 106 patients included in the study, 41 (38.7%) patients died, and 69 (65.1%) patients had poor prognosis when discharged from NCU. The four time points within 72 h of admission to the NCU were equivalent for each scales predictive power, except that 0 h was the best for each scale in predicting outcomes of patients with right-hemisphere lesions. Nonsignificant difference was found between GCS-M AUCs and GCS AUCs in predicting death at 0 h (0.721 vs. 0.717, Z = 0.135, P = 0.893) and 72 h (0.730 vs. 0.765, Z = 1.887, P = 0.060), in predicting poor prognosis at 0 h (0.827 vs. 0.819, Z = 0.395, P = 0.693), 24 h (0.771 vs. 0.760, Z = 0.944, P = 0.345), 48 h (0.732 vs. 0.741, Z = 0.593, P = 0.590), and 72 h (0.775 vs. 0.780, Z = 0.302, P = 0.763). AUCs in predicting death for patients with left-hemisphere lesions ranged from 0.700 to 0.804 for GCS-M and from 0.700 to 0.824 for GCS, in predicting poor prognosis ranged from 0.841 to 0.969 for GCS-M and from 0.875 to 0.969 for GCS, with no significant difference between GCS-M AUCs and GCS AUCs within 72 h (P > 0.05). No significant difference between GCS-M AUCs and GCS AUCs was found in predicting death (0.964 vs. 0.964, P = 1.000) and poor prognosis (1.000 vs. 1.000, P = 1.000) for patients with right-hemisphere lesions at 0 h. AUCs in predicting death for patients with brainstem or cerebella were poor for GCS-M (<0.700), in predicting poor prognosis ranged from 0.727 to 0.801 for GCS-M and from 0.704 to 0.820 for GCS, with no significant difference between GCS-M AUCs and GCS AUCs within 72 h (P > 0.05). The SMS AUCs (<0.700) in predicting outcomes were poor. Conclusions: The GCS-M approaches the same test performance as the GCS in assessing the prognosis of intubated acute severe cerebral vascular disease patients. The GCS-M could be accurately and reliably applied in patients with hemisphere lesions, but caution must be taken for patients with brainstem or cerebella lesions.

Analysis on the training effect of criteria and practical guidance for determination of brain death: evoked potentials

Objective To analyze the training results of short-latency somatosensory-evoked potential (SLSEP) for brain death determination and to improve the training program. Methods A total of 101 trainees received theoretical training, simulation skills training, bedside skills training and test analysis for SLSEP in brain death determination. The composition of trainees was analyzed and the error rates of 6 knowledge points were calculated. Univariate and multivariate backward Logistic regression analyses were used to analyze the influence of factors including sex, age, specialty, professional category, professional qualification and hospital level, on the error rates. Results Among them, trainees of 30-49 years old occupied 76.24% (77/101), most of them were from third grade, grade A hospitals (98.02%, 99/101), and 78 trainees (77.23%) were from Department of Neurology. There were 82 clinicians (81.19%), 31 (30.69%) had senior certificate and 42 (41.58%) had intermediate certificate. Total error rate of 6 knowledge points was 4.50% (91/2020). Of the 6 knowledge points, the error rate of pitfalls was the highest (9.41%, 19/202), followed by result determination (5.94% , 12/202), recording techniques (4.75% , 24/505), procedures (3.96%, 32/808), sequence of confirmatory tests (1.98%, 2/101) and environmental conditions (0.99%, 2/202). Univariate and multivariate Logistic regression analyses showed that age ( OR = 1.566, 95% CI: 1.116-2.197; P = 0.009) and professional qualification ( OR = 1.669, 95% CI: 1.163-2.397; P = 0.005) were independent risk factors associated with high error rates. Conclusions The differences between brain death determination and routine check of SLSEP should be paid more attention to improve the quality of determination for brain death by SLSEP. DOI: 10.3969/j.issn.1672-6731.2015.12.007