Biomarkers of brain injury after cardiac arrest; a statistical analysis plan from the TTM2 trial biobank investigators

Background: Several biochemical markers in blood correlate with the magnitude of brain injury and may be used to predict neurological outcome after cardiac arrest. We present a protocol for the evaluation of prognostic accuracy of brain injury markers after cardiac arrest. The aim is to define the best predictive marker and to establish clinically useful cut-off levels for routine implementation. Methods: Prospective international multicenter trial within the Targeted Hypothermia versus Targeted Normothermia after Out-of-Hospital Cardiac Arrest (TTM2) trial in collaboration with Roche Diagnostics International AG. Samples were collected 0, 24, 48, and 72 hours after randomisation (serum) and 0 and 48 hours after randomisation (plasma), and pre-analytically processed at each site before storage in a central biobank. Routine markers neuron-specific enolase (NSE) and S100B, and neurofilament light, total-tau and glial fibrillary acidic protein will be batch analysed using novel Elecsys® electrochemiluminescence immunoassays on a Cobas e601 instrument. Results: Statistical analysis will be reported according to the Standards for Reporting Diagnostic accuracy studies (STARD) and will include comparisons for prediction of good versus poor functional outcome at six months post-arrest, by modified Rankin Scale (0–3 vs. 4–6), using logistic regression models and receiver operating characteristics curves, evaluation of mortality at six months according to biomarker levels and establishment of cut-off values for prediction of poor neurological outcome at 95–100% specificities. Conclusions: This prospective trial may establish a standard methodology and clinically appropriate cut-off levels for the optimal biomarker of brain injury which predicts poor neurological outcome after cardiac arrest

Redescription of the Antarctic springtail Desoria klovstadi using morphological and molecular evidence

Isotoma klovstadi Carpenter, 1902 was one of the first Collembola described from the Antarctic continent. It was first collected in November 1899 during the British Antarctic Expedition on the north coast of Victoria Land in the Ross Sea region. It is now known to occur in an extensive area of northern Victoria Land, including the offshore Possession, Coulman, and Foyn Islands. More recently, L klovstadi was moved to the genus Gnathisotoma Cassagnau, 1957 and has been included in this genus in an unpublished checklist (online) of all described Collembola. Here, we redescribe the species and use morphological and molecular (COI and 18S genes) evidence to investigate its affinities within the Isotominae. We show that it does not belong to Gnathisotoma, or Isotoma s. str. (the viridis group) as currently conceived, but is likely to be part of the species complex of Isotoma s. lat. We discuss reasons for placing it in the genus Desoria Nicolet, 1841. Our results reinforce the already high level of endemicity in the Antarctic fauna and emphasise the value of both morphological and molecular studies in examining relict Gondwanan taxa and their evolutionary relationships with those of other Southern Hemisphere continents

Predicting neurological outcome after out-of-hospital cardiac arrest with cumulative information; development and internal validation of an artificial neural network algorithm

Background: Prognostication of neurological outcome in patients who remain comatose after cardiac arrest resuscitation is complex. Clinical variables, as well as biomarkers of brain injury, cardiac injury, and systemic inflammation, all yield some prognostic value. We hypothesised that cumulative information obtained during the first three days of intensive care could produce a reliable model for predicting neurological outcome following out-of-hospital cardiac arrest (OHCA) using artificial neural network (ANN) with and without biomarkers. Methods: We performed a post hoc analysis of 932 patients from the Target Temperature Management trial. We focused on comatose patients at 24, 48, and 72 h post-cardiac arrest and excluded patients who were awake or deceased at these time points. 80% of the patients were allocated for model development (training set) and 20% for internal validation (test set). To investigate the prognostic potential of different levels of biomarkers (clinically available and research-grade), patients’ background information, and intensive care observation and treatment, we created three models for each time point: (1) clinical variables, (2) adding clinically accessible biomarkers, e.g., neuron-specific enolase (NSE) and (3) adding research-grade biomarkers, e.g., neurofilament light (NFL). Patient outcome was the dichotomised Cerebral Performance Category (CPC) at six months; a good outcome was defined as CPC 1–2 whilst a poor outcome was defined as CPC 3–5. The area under the receiver operating characteristic curve (AUROC) was calculated for all test sets. Results: AUROC remained below 90% when using only clinical variables throughout the first three days in the ICU. Adding clinically accessible biomarkers such as NSE, AUROC increased from 82 to 94% (p < 0.01). The prognostic accuracy remained excellent from day 1 to day 3 with an AUROC at approximately 95% when adding research-grade biomarkers. The models which included NSE after 72 h and NFL on any of the three days had a low risk of false-positive predictions while retaining a low number of false-negative predictions. Conclusions: In this exploratory study, ANNs provided good to excellent prognostic accuracy in predicting neurological outcome in comatose patients post OHCA. The models which included NSE after 72 h and NFL on all days showed promising prognostic performance

Serum tau and neurological outcome in cardiac arrest

Objective: To test serum tau as a predictor of neurological outcome after cardiac arrest. Methods: We measured the neuronal protein tau in serum at 24, 48, and 72 hours after cardiac arrest in 689 patients in the prospective international Target Temperature Management trial. The main outcome was poor neurological outcome, defined as Cerebral Performance Categories 3–5 at 6 months. Results: Increased tau was associated with poor outcome at 6 months after cardiac arrest (median = 38.5, interquartile range [IQR] = 5.7–245ng/l in poor vs median = 1.5, IQR = 0.7–2.4ng/l in good outcome, for tau at 72 hours, p < 0.0001). Tau improved prediction of poor outcome compared to using clinical information (p < 0.0001). Tau cutoffs had low false-positive rates (FPRs) for good outcome while retaining high sensitivity for poor outcome. For example, tau at 72 hours had FPR = 2% (95% CI = 1–4%) with sensitivity = 66% (95% CI = 61–70%). Tau had higher accuracy than serum neuron-specific enolase (NSE; the area under the receiver operating characteristic curve was 0.91 for tau vs 0.86 for NSE at 72 hours, p = 0.00024). During follow-up (up to 956 days), tau was significantly associated with overall survival. The accuracy in predicting outcome by serum tau was equally high for patients randomized to 33 °C and 36 °C targeted temperature after cardiac arrest. Interpretation: Serum tau is a promising novel biomarker for prediction of neurological outcome in patients with cardiac arrest. It may be significantly better than serum NSE, which is recommended in guidelines and currently used in clinical practice in several countries to predict outcome after cardiac arrest. Ann Neurol 2017;82:665–675

Serum markers of brain injury can predict good neurological outcome after out-of-hospital cardiac arrest

Purpose: The majority of unconscious patients after cardiac arrest (CA) do not fulfill guideline criteria for a likely poor outcome, their prognosis is considered “indeterminate”. We compared brain injury markers in blood for prediction of good outcome and for identifying false positive predictions of poor outcome as recommended by guidelines. Methods: Retrospective analysis of prospectively collected serum samples at 24, 48 and 72 h post arrest within the Target Temperature Management after out-of-hospital cardiac arrest (TTM)-trial. Clinically available markers neuron-specific enolase (NSE) and S100B, and novel markers neurofilament light chain (NFL), total tau, ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) and glial fibrillary acidic protein (GFAP) were analysed. Normal levels with a priori cutoffs specified by reference laboratories or defined from literature were used to predict good outcome (no to moderate disability, Cerebral Performance Category scale 1–2) at 6 months. Results: Seven hundred and seventeen patients were included. Normal NFL, tau and GFAP had the highest sensitivities (97.2–98% of poor outcome patients had abnormal serum levels) and NPV (normal levels predicted good outcome in 87–95% of patients). Normal S100B and NSE predicted good outcome with NPV 76–82.2%. Normal NSE correctly identified 67/190 (35.3%) patients with good outcome among those classified as “indeterminate outcome” by guidelines. Five patients with single pathological prognostic findings despite normal biomarkers had good outcome. Conclusion: Low levels of brain injury markers in blood are associated with good neurological outcome after CA. Incorporating biomarkers into neuroprognostication may help prevent premature withdrawal of life-sustaining therapy