Association of Posttraumatic Epilepsy With Long-term Functional Outcomes in Individuals With Severe Traumatic Brain Injury.

BACKGROUND AND OBJECTIVE: Nearly one-third of patients with severe traumatic brain injury (TBI) develop posttraumatic epilepsy (PTE). The relationship between PTE and long-term outcomes is unknown. We tested whether, after controlling for injury severity and age, PTE is associated with worse functional outcomes after severe TBI. METHODS: We performed a retrospective analysis of a prospective database of patients with severe TBI treated from 2002 through 2018 at a single level 1 trauma center. Glasgow Outcome Scale (GOS) was collected at 3, 6, 12, and 24 months postinjury. We used repeated-measures logistic regression predicting GOS, dichotomized as favorable (GOS 4-5) and unfavorable (GOS 1-3), and a separate logistic model predicting mortality at 2 years. We used predictors as defined by the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) base model (i.e., age, pupil reactivity, and GCS motor score), PTE status, and time. RESULTS: Of 392 patients who survived to discharge, 98 (25%) developed PTE. The proportion of patients with favorable outcomes at 3 months did not differ between those with and without PTE (23% [95% Confidence Interval [CI]: 15%-34%] vs 32% [95% CI: 27%-39%]; p = 0.11) but was significantly lower at 6 (33% [95% CI: 23%-44%] vs 46%; [95% CI: 39%-52%] p = 0.03), 12 (41% [95% CI: 30%-52%] vs 54% [95% CI: 47%-61%]; p = 0.03), and 24 months (40% [95% CI: 47%-61%] vs 55% [95% CI: 47%-63%]; p = 0.04). This was driven by higher rates of GOS 2 (vegetative) and 3 (severe disability) outcomes in the PTE group. By 2 years, the incidence of GOS 2 or 3 was double in the PTE group (46% [95% CI: 34%-59%]) compared with that in the non-PTE group (21% [95% CI: 16%-28%]; p < 0.001), while mortality was similar (14% [95% CI: 7%-25%] vs 23% [95% CI: 17%-30%]; p = 0.28). In multivariate analysis, patients with PTE had lower odds of favorable outcome (odds radio [OR] 0.1; 95% CI: 0.1-0.4; p < 0.001), but not mortality (OR 0.9; 95% CI: 0.1-1.9; p = 0.46). DISCUSSION: Posttraumatic epilepsy is associated with impaired recovery from severe TBI and poor functional outcomes. Early screening and treatment of PTE may improve patient outcomes.

Time to Awakening and Self-Fulfilling Prophecies After Cardiac Arrest.

OBJECTIVES: Withdrawal of life-sustaining therapies for perceived poor neurologic prognosis (WLST-N) is common after resuscitation from cardiac arrest and may bias outcome estimates from models trained using observational data. We compared several approaches to outcome prediction with the goal of identifying strategies to quantify and reduce this bias. DESIGN: Retrospective observational cohort study. SETTING: Two academic medical centers ("UPMC" and "University of Alabama Birmingham" [UAB]). PATIENTS: Comatose adults resuscitated from cardiac arrest. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: As potential predictors, we considered clinical, laboratory, imaging, and quantitative electroencephalography data available early after hospital arrival. We followed patients until death, discharge, or awakening from coma. We used penalized Cox regression with a least absolute shrinkage and selection operator penalty and five-fold cross-validation to predict time to awakening in UPMC patients and then externally validated the model in UAB patients. This model censored patients after WLST-N, considering subsequent potential for awakening to be unknown. Next, we developed a penalized logistic model predicting awakening, which treated failure to awaken after WLST-N as a true observed outcome, and a separate logistic model predicting WLST-N. We scaled and centered individual patients' Cox and logistic predictions for awakening to allow direct comparison and then explored the difference in predictions across probabilities of WLST-N. Overall, 1,254 patients were included, and 29% awakened. Cox models performed well (mean area under the curve was 0.93 in the UPMC test sets and 0.83 in external validation). Logistic predictions of awakening were systematically more pessimistic than Cox-based predictions for patients at higher risk of WLST-N, suggesting potential for self-fulfilling prophecies to arise when failure to awaken after WLST-N is considered as the ground truth outcome. CONCLUSIONS: Compared with traditional binary outcome prediction, censoring outcomes after WLST-N may reduce potential for bias and self-fulfilling prophecies.

Frequency of Withdrawal of Life-Sustaining Therapy for Perceived Poor Neurologic Prognosis.

To measure the frequency of withdrawal of life-sustaining therapy for perceived poor neurologic prognosis among decedents in hospitals of different sizes and teaching statuses. DESIGN: We performed a multicenter, retrospective cohort study. SETTING: Four large teaching hospitals, four affiliated small teaching hospitals, and nine affiliated nonteaching hospitals in the United States. PATIENTS: We included a sample of all adult inpatient decedents between August 2017 and August 2019. MEASUREMENTS AND MAIN RESULTS: We reviewed inpatient notes and categorized the immediately preceding circumstances as withdrawal of life-sustaining therapy for perceived poor neurologic prognosis, withdrawal of life-sustaining therapy for nonneurologic reasons, limitations or withholding of life support or resuscitation, cardiac death despite full treatment, or brain death. Of 2,100 patients, median age was 71 years (interquartile range, 60-81 yr), median hospital length of stay was 5 days (interquartile range, 2-11 d), and 1,326 (63%) were treated at four large teaching hospitals. Withdrawal of life-sustaining therapy for perceived poor neurologic prognosis occurred in 516 patients (25%) and was the sole contributing factor to death in 331 (15%). Withdrawal of life-sustaining therapy for perceived poor neurologic prognosis was common in all hospitals: 30% of deaths at large teaching hospitals, 19% of deaths in small teaching hospitals, and 15% of deaths at nonteaching hospitals. Withdrawal of life-sustaining therapy for perceived poor neurologic prognosis happened frequently across all hospital units. Withdrawal of life-sustaining therapy for perceived poor neurologic prognosis contributed to one in 12 deaths in patients without a primary neurologic diagnosis. After accounting for patient and hospital characteristics, significant between-hospital variability in the odds of withdrawal of life-sustaining therapy for perceived poor neurologic prognosis persisted. CONCLUSIONS: A quarter of inpatient deaths in this cohort occurred after withdrawal of life-sustaining therapy for perceived poor neurologic prognosis. The rate of withdrawal of life-sustaining therapy for perceived poor neurologic prognosis occurred commonly in all type of hospital settings. We observed significant unexplained variation in the odds of withdrawal of life-sustaining therapy for perceived poor neurologic prognosis across participating hospitals.

Differences in Prehospital Patient Assessments for Pediatric Versus Adult Patients.

OBJECTIVE: To evaluate whether completion of vital signs assessments in pediatric transports by emergency medical services (EMS) differs by patient age. STUDY DESIGN: We reviewed records by 20 agencies in a regional EMS system in Southwestern Pennsylvania between April 1, 2013 and December 31, 2016. We abstracted demographics, vital signs (systolic blood pressure, heart rate, respiratory rate), clinical, and transport characteristics. We categorized age as neonates (≤30 days), infants (1 month to <1 year), toddler (1 to <2 years), early childhood (2 to <6 years), middle childhood (6 to <12 years), adolescent (12 to <18 years), and adult (≥18 years). We used unadjusted and adjusted logistic regression to test if age group was associated with vital signs documentation, reporting of Glasgow Coma Scale and pain scale after trauma, and recording of oxygen saturation and breath sounds in respiratory complaints, using adults as the reference group. RESULTS: In total, 371 746 cases (21 883 pediatric, 5.9%) were included. In adjusted analysis, most pediatric categories had reduced odds of complete vitals documentation (percent, OR, 95% CI): neonates (49.6%, 0.02, 0.02-0.03), infants (68.2%, 0.04, 0.03-0.04), toddlers (78.1%, 0.07, 0.06-0.07), early childhood (87.4%, 0.13, 0.12-0.15), and middle childhood (95.3%, 0.54, 0.46-0.63). Pain score documentation was lower in children after trauma (OR 0.80, 95%CI 0.76-0.85), and oxygen saturation documentation was lower in children with respiratory complaints (OR 0.20, 95%CI 0.18-0.25). CONCLUSIONS: Pediatric patients were at increased risk of lacking vital signs documentation during prehospital care. This represents a critical area for education and quality improvement.

Clinically distinct electroencephalographic phenotypes of early myoclonus after cardiac arrest.

OBJECTIVE: We tested the hypothesis that there are readily classifiable electroencephalographic (EEG) phenotypes of early postanoxic multifocal myoclonus (PAMM) that develop after cardiac arrest. METHODS: We studied a cohort of consecutive comatose patients treated after cardiac arrest from January 2012 to February 2015. For patients with clinically evident myoclonus before awakening, 2 expert physicians reviewed and classified all EEG recordings. Major categories included: Pattern 1, suppression-burst background with high-amplitude polyspikes in lockstep with myoclonic jerks; and Pattern 2, continuous background with narrow, vertex spike-wave discharges in lockstep with myoclonic jerks. Other patterns were subcortical myoclonus and unclassifiable. We compared population characteristics and outcomes across these EEG subtypes. RESULTS: Overall, 401 patients were included, of whom 69 (16%) had early myoclonus. Among these patients, Pattern 1 was the most common, occurring in 48 patients (74%), whereas Pattern 2 occurred in 8 patients (12%). The remaining patients had subcortical myoclonus (n = 2, 3%) or other patterns (n = 7, 11%). No patients with Pattern 1, subcortical myoclonus, or other patterns survived with favorable outcome. By contrast, 4 of 8 patients (50%) with Pattern 2 on EEG survived, and 4 of 4 (100%) survivors had favorable outcomes despite remaining comatose for 1 to 2 weeks postarrest. INTERPRETATION: Early PAMM is common after cardiac arrest. We describe 2 distinct patterns with distinct prognostic significances. For patients with Pattern 1 EEGs, it may be appropriate to abandon our current clinical standard of aggressive therapy with conventional antiepileptic therapy in favor of early limitation of care or novel neuroprotective strategies. Ann Neurol 2016;80:175-184.

Serum Neutrophil Gelatinase-Associated Lipocalin Predicts Survival After Resuscitation From Cardiac Arrest.

OBJECTIVES: In the first days after cardiac arrest, accurate prognostication is challenging. Serum biomarkers are a potentially attractive adjunct for prognostication and risk stratification. Our primary objective in this exploratory study was to identify novel early serum biomarkers that predict survival after cardiac arrest earlier than currently possible. DESIGN: Prospective, observational study. SETTING: A single academic medical center. SUBJECTS: Adult subjects who sustained cardiac arrest with return of spontaneous circulation. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: We obtained blood samples from each subject at enrollment, 6, 12, 24, 48, and 72 hours after return of spontaneous circulation. We measured the serum levels of novel biomarkers, including neutrophil gelatinase-associated lipocalin, high-mobility group protein B1, intracellular cell adhesion molecule-1, and leptin, as well as previously characterized biomarkers, including neuron-specific enolase and S100B protein. Our primary outcome of interest was survival-to-hospital discharge. We compared biomarker concentrations at each time point between survivors and nonsurvivors and used logistic regression to test the unadjusted associations of baseline clinical characteristics and enrollment biomarker levels with survival. Finally, we constructed a series of adjusted models to explore the independent association of each enrollment biomarker level with survival. A total of 86 subjects were enrolled. Enrollment levels of high-mobility group protein B1, neutrophil gelatinase-associated lipocalin, and S100B were higher in nonsurvivors than survivors. Enrollment leptin, neuron-specific enolase, and intracellular cell adhesion molecule-1 levels did not differ between nonsurvivors and survivors. The discriminatory power of enrollment neutrophil gelatinase-associated lipocalin level was the greatest (c-statistic, 0.78 [95% CI, 0.66-0.90]) and remained stable across all time points. In our adjusted models, enrollment neutrophil gelatinase-associated lipocalin level was independently associated with survival even after controlling for the development of acute kidney injury, and its addition to clinical models improved overall predictive accuracy. CONCLUSIONS: Serum neutrophil gelatinase-associated lipocalin levels are strongly predictive of survival-to-hospital discharge after cardiac arrest.