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Neuron-specific enolase and S-100b in prolonged targeted temperature management after cardiac arrest: A randomised study
Resuscitation 122 (2018) 79–86
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Clinical paper
Neuron-specific enolase and S-100b in prolonged targeted temperature management after cardiac arrest: A randomised study夽 Christophe Henri Valdemar Duez a,b,∗ , Anders Morten Grejs a,b , Anni Nørgaard Jeppesen a,b , Anne Dilani Schrøder c , Eldar Søreide d,e , Jørgen Feldbæk Nielsen f , Hans Kirkegaard b a
Department of Anaesthesiology and Intensive Care Medicine, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus N, Denmark Research Centre for Emergency Medicine, Aarhus University Hospital, Nørrebrogade 44, Building 1B, 1st floor, 8000, Aarhus C, Denmark c Department of Clinical Biochemistry, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus N, Denmark d Critical Care and Anaesthesiology Research Group, Stavanger University Hospital, Norway e Department of Clinical Medicine, University of Bergen, Bergen, Norway f Hammel Neurorehabilitation and Research Centre (HNRC), Denmark b
a r t i c l e
i n f o
Article history: Received 7 August 2017 Received in revised form 14 November 2017 Accepted 19 November 2017 Keywords: Neuron-specific enolase S-100b Prognostication Prolonged targeted temperature management Cardiac arrest Therapeutic hypothermia
a b s t r a c t Background: We aimed to investigate the impact of prolonged targeted temperature management (TTM) in cardiac arrest patients on release of serum levels of NSE and S-100b and their prognostic performances. Methods: This is a substudy of the Targeted Temperature Management for 24 vs 48 h trial. NSE and S-100b levels were analysed retrospectively in serum samples collected upon admission, at 24, 48, and 72 h after reaching the target temperature of 33 ± 1 ◦ C. The primary outcome was biomarker serum concentrations and secondary outcome was the cerebral performance category score after 6 months. Results: 115 patients from two centres were analysed. NSE and S-100b levels did not differ between TTM groups at any single time-point. Poor outcome patients had higher biomarker levels at 24, 48, and 72 h: NSE: 9.73 (7.2; 10.9) versus 20.40 (12.7; 27.2), 8.86 (6.6; 9.6) versus 17.47 (11.1; 37.3) and 6.23 (5.3; 8.5) versus 31.05 (12.8; 52.5) respectively and S-100b: 0.09 (0.07; 0.11) versus 0.23 (0.19; 0.39), 0.08 (0.07; 0.09) versus 0.18 (0.15; 0.33) and 0.07 (0.06; 0.08) versus 0.13 (0.09; 0.23). The daily changes in NSE from admission to Day 2 after the cardiac arrest (CA) were also related to the outcome (p = 0.003 and p = 0.02). The best prediction of outcome was found at 72 h for NSE and at 24 h as well as 48 h for S100b. Conclusions: No clinically relevant differences were found in the levels of NSE or S-100b between standard and prolonged TTM. Prognostic reliability of NSE and S-100b was unaltered by prolonged TTM. © 2017 Published by Elsevier Ireland Ltd.
Introduction Out-of-hospital cardiac arrest (OHCA) affects an estimated 400,000 people in Europe each year [1], and with a mere 10% survival rate, it is a major cause of death. Two landmark studies from 2002 [2,3] demonstrated that targeted temperature management (TTM) at 33 ◦ C for 12–24 h improved the neurological outcome and survival in comatose OHCA patients admitted to the intensive care unit (ICU). Consequently, TTM at 33 ◦ for 24 h became the standard
夽 A Spanish translated version of the abstract of this article appears as Appendix in the final online version at https://doi.org/10.1016/j.resuscitation.2017.11.052 ∗ Corresponding author at: Intensive Care Research Unit/Research Centre for Emergency Medicine Palle Juul Jensens Boulevard 99, Aarhus University Hospital, DK-8200, Aarhus N, Denmark. E-mail address: [email protected] (C.H.V. Duez). https://doi.org/10.1016/j.resuscitation.2017.11.052 0300-9572/© 2017 Published by Elsevier Ireland Ltd.
treatment in post-cardiac arrest therapy worldwide, albeit with a low level of evidence. The TTM-trial from 2013 [4], randomising 950 OHCA patients, demonstrated that there was no difference in the neurological outcome, whether the patients were cooled to 33 or 36 ◦ C. As a result, the most recent guidelines now recommend TTM at 32–36 ◦ C for at least 24 h in OHCA patients [5]. Besides the optimal TTM temperature, duration of TTM is another big question within post-resuscitation care research. In search of an answer to this question, a study including 355 OHCA patients [6] reported no difference in the neurological outcome of prolonged TTM for 48 h versus standard duration of TTM for 24 h. The introduction of TTM changed the reliability of the known prognosticators, and the importance of further investigations on prognosticators in this new setting is therefore important to secure safety in prognostication. The blood concentration of the two biomarkers, neuron-specific enolase (NSE) and protein S-100b, are
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associated with the neurological outcome and play an important role in prognostication due to their almost universal accessibility and low costs. The two largest studies on NSE and S-100b levels in OHCA patients to date [7,8] reported that an intervention in the 33–36 ◦ C span did not affect the levels of the two biomarkers to a clinically relevant degree, albeit the levels of S-100b were higher in patients treated with TTM to 33 ◦ C at two of the three sample time-points. The aim of the present study was to investigate whether prolonged TTM would reduce NSE and S-100b serum levels or cause changes in the biomarker levels over time. Furthermore, we wanted to explore the prognostic performance of the two biomarkers at specific time-points as well as their progression over time from one sample to the next. We hypothesised that prolonged TTM for 48 h would reduce the serum levels of NSE and S-100b, as compared to the standard 24-h duration of TTM. Methods Patients All the patients included in the present study were a subset of the patients (n = 355) included in the randomised multicentre study, “Targeted Temperature Management for 48 vs 24 h and Neurologic Outcome After Out-of-Hospital Cardiac Arrest: A Randomized Clinical Trial” (the TTH48 trial) [6]. TTH48 compares the effect on the neurological outcomes of 24 vs. 48 h of TTM at 33 ± 1 ◦ C. In the present prospective study, a total of 159 patients were enrolled in the ICUs at Aarhus University Hospital, Denmark, and Stavanger University Hospital, Norway. The inclusion criteria were the following: OHCA with a presumed cardiac origin, Glasgow Coma Scale below 8, sustained spontaneous circulation after resuscitation (no need for cardiac compressions for 20 min and clinical signs of circulation), aged between 18 and 80 years. The exclusion criteria were as follows: estimated time from collapse to return of spontaneous circulation (ROSC) of more than 60 min, terminal disease, severe coagulopathy, unwitnessed OHCA with asystole as first rhythm, time from cardiac arrest to the initiation of cooling of more than 240 min, pregnancy, previous neurological disease with cognitive impairment, persistent cardiogenic shock, systolic blood pressure below 80 mmHg despite vasoactive treatment and/or aortic balloon pump intervention, suspected or confirmed acute intracerebral bleeding/acute stroke, acute coronary artery bypass surgery, or lack of consent [9]. All the patients were treated either with TTM for 48 h (TTM48) or standard duration TTM for 24-h (TTM24). Either surface or intravascular feedback cooling systems were employed to maintain target temperature (TT). The rewarming rate was 0.5 ◦ C h−1 . The body core temperature was continuously monitored in the urinary bladder throughout TTM. The patients were sedated with intravenous infusions of propofol/midazolam and remifentanil/fentanyl until normothermia was reached. Clinical data were collected using the patients’ medical records and the patient data management systems. Prehospital cardiac arrest data were collected according to the Utstein guidelines [10]. The study was approved by the Danish Data Protection Agency and the Central Denmark Region Committees on Health Research Ethics (case number 20110022) and the Regional Ethics Committee of Western Norway (ref 2013/1486). Outcome measure The primary outcome measure was the serum concentrations of NSE and S-100b. The levels of NSE and S-100b were assessed at four time-points. The first blood sample was drawn upon patient
admission while the second sample was drawn 24 h (t24) after the patient reached the TT. The time was measured from the moment when the core temperature breached the 34 ◦ C threshold. The third sample was drawn at 48 h (t48) after reaching the TT and the fourth sample at 72 h after obtaining the TT (t72). The secondary outcome was the cerebral performance categories (CPC) [10,11] at 6 months. The CPC score was assessed by a researcher blinded to the intervention, either by a phone interview at Aarhus or by a face-to-face interview at Stavanger. The CPC score is defined as follows: CPC 1: no neurological deficit, CPC 2: mild to moderate dysfunction, CPC 3: severe dysfunction, CPC 4: coma, and CPC 5: death. The outcome was dichotomised so that a CPC score of 1–2 was considered a good neurological outcome while a CPC score of 3–5 was considered a poor outcome. Blood samples Blood samples for the NSE and S100b analyses were centrifuged within an hour after the collection and the serum was stored at −80 C◦ until analysis. Samples were analysed a posteriori at a single core lab in two batches, using the Cobas E601 system with an electrochemiluminescence immunoassay (Roche Diagnostics, Mannheim, Germany). Measurement ranges were 0.3–740 g/l for NSE and 0.02–39 g/l for S-100b. The level of hemolysis was assessed through a fotometric measurement of the absorbance at two different wavelengths (570 nanometers (nm) and 600 nm). Statistical analysis The baseline characteristics were presented as medians and interquartile ranges for continuous data and as counts and percentages for categorical variables. They were compared between the TTM groups using the Mann-Whitney U test. The biomarker levels were presented as medians with 95% confidence intervals (CI). Sensitivity and specificity were calculated at different cut-off values at the specific sample time-points and for changes over time using a nonparametric ROC analysis, reported as percentages with 95% CI. A repeated measures mixed model was employed to test for the differences in the biomarker levels between the two TTM groups at each sample time-point. The same process was followed to test for progression over time in the serum levels of the biomarkers through all four samples using a test for parallel curves. A multiple logistic regression adjusted for minutes to ROSC, primary rhythm (shockable or non-shockable), and age was used to test for a relationship between good (CPC 1–2) and poor neurologic outcomes (CPC 3–5) at 6 months for each of the four samples (admission, t24, t48, and t72) and for changes in serum levels from one sample to the next. Multiple imputation to adjust for the missing samples was not employed. The prognostic performance was evaluated by the unadjusted areas under the receiver operating characteristic curves (AUROCs) at each sample time and for changes in the serum levels over time. A power calculation was not performed, since we aimed to include as many patients as possible from the main TTH48-trial. Statistical analysis was performed using STATA 13.1 (StataCorp LP, TX, USA). A p-value < 0.05 was considered to indicate statistical significance. Results A total of 159 patients treated with TTM for 24 or 48 h at 33 ◦ C were enrolled in the TTH48 trial during the study period, at both Aarhus and Stavanger. Blood samples were collected from 128 of these patients; 115 were included in the final statistical analysis (Fig. 1). At the 6-month follow-up, 79 patients (69%) had a good neurological outcome (CPC score 1 or 2) while 36 had a poor neurological outcome (CPC score 3–5). No significant differences were
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Fig. 1. Study flowchart. a) Presentation of patients enrolled in the main TTH48 trial and in this substudy. b): Sample flowchart presenting reasons for missing and excluded samples. TTM24 = Targeted Temperature Management for 24 h. TTM48 = Targeted Temperature Management for 48 h. CPC = cerebral performance categories outcome scale.
Table 1 Baseline characteristics. pooled (n)
Patients Age, years (median and IQR) Male Bystander CPR performed Primary shockable rhythm Time to ROSC, minutes (median and IQR) PCI performed previous AMI Diabetes Mellitus
%
TTM24 (n)
115 61 (53–69) 98 85% 91 79% 98 85% 20 (15–31) 43 21 20
37% 18% 17%
%
56 61 (53–69) 49 44 47 20 (14–32)
49%
21 11 9
18% 10% 8%
88% 79% 84%
TTM48 (n)
%
59 61 (53–69) 49 47 51 21 (16–28)
51% 83% 80% 86%
22 10 11
19% 9% 10%
p-value
Missed inclusion n
% 28%
0.81 0.60 0.75 0.80 0.77
44 65 (53–72) 38 39 35 24 (17–30)
p-value
86% 89% 80%
0.28 0.65 0.37 0.77 0.62
0.63 0.68 0.72
26 6 8
59% 14% 18%
<0.001 0.63 0.81
TTM24 = Targeted Temperature Management for 24 h. TTM48 = Targeted Temperature Management for 48 h. Values are number (n) or median and percent of total (%). IQR = inter quartile range, ROSC = return of spontaneous circulation. CPR = cardiopulmonary resuscitation, PCI = percutaneous coronary intervention, AMI = acute myocardial infarction. P-values are the results of Mann-Whitney U test between TTM groups. The “Missed inclusion” columns compares the 44 patients missed for inclusion with the 115 included patients.
found in the baseline characteristics (Table 1) or in the neurological outcome measured by CPC between the two TTM groups (p = 0.55). No significant differences were found between the 44 missed inclusions and the 115 analysed patients in baseline characteristics or neurological outcome (p = 0.97), except for the number of performed percutaneous coronary interventions (Table 1). Biomarker levels in prolonged vs standard duration of TTM We found no difference between prolonged and standard duration of TTM at any sample time-point in NSE or S-100b serum concentrations (Table 2). The levels of NSE and S-100b generally decreased over time, from admission to t72 with a marked decrease from admission to t24 (Fig. 2). The progression of NSE levels over
time was unaffected by the prolonged TTM (p = 0.20), but a difference between the TTM-groups was found for S-100b (p < 0.001). Prediction of neurological outcome by biomarker levels Since no difference in the biomarker levels between the two TTM groups in the present study could be demonstrated, the data for prognostication analyses were pooled. NSE and S-100b levels were higher in patients with poor outcome at all time-points (Fig. 2). For NSE, levels were 19.86 (16.8; 23.4) versus 24.40 (19.8; 30.0) at admission (p = 0.88), 9.73 (7.2; 10.9) versus 20.40 (12.7; 27.2) at t24 (p = 0.01), 8.86 (6.6; 9.6) versus 17.47 (11.1; 37.3) at t48 (p = 0.01) and 6.23 (5.3; 8.5) versus 31.05 (12.8; 52.5) at t72 (p = 0.001). For S-100b levels were: 0.83 (0.63; 1.10) versus
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Table 2 Repeated measures mixed model analysis. Biomarker levels between TTM groups at each sample time-point TTM24 Estimated Median (g/l) NSE arrival NSE 24 h (t24) NSE 48 h (t48) NSE 72 h (t72) S100b arrival S100b 24 h (t24) S100b 48 h (t48) S100b 72 h (t72)
NSE arr-t24 NSE t24−t48 NSE t48-t72 S100b arr-t24 S100b t24-t48 S100b t48-t72
Mixed model analysis
TTM48 95% CI
n
Estimated Median (g/l)
17.8 14.4; 21.2 49 22.8 12.4 9.5; 15.4 55 11.4 12.3 8.6; 16.1 50 10.0 7.6; 14.4 11.0 48 9.5 0.86 0.59; 1.14 49 0.93 0.17 0.12; 0.23 55 0.13 0.15 0.11; 0.20 51 0.11 0.09 0.07; 0.12 49 0.1 Median change in biomarker levels from sample to sample between TTM groups −6.19 −0.26 −3.04 −0.57 −0.01 −0.04
−9.2; 2.0 −2.3; 2.6 −4.2; 0.78 −0.94; −0.24 −0.04; 0.002 −0.05; −0.02
48 49 45 48 50 47
−9.00 −1.18 −0.15 −0.74 −0.02 0.003
95% CI
n
exp(b)
18.6; 27.0 8.8; 14.0 7.1; 13.0 6.7; 12.4 0.64; 1.21 0.09; 0.17 0.08; 0.14 0.08; 0.13
51 58 55 52 53 58 55 54
−12.8; −6.3 −2.7; 0.26 −1.0; 0.74 −1.2; −0.47 −0.03; −0.01 −0.003; 0.01
50 54 52 52 54 54
1.28 0.98; 1.67 0.07 0.92 0.66; 1.27 0.60 0.81 0.53; 1.24 0.34 0.87 0.56; 1.34 0.53 1.07 0.69; 1.68 0.75 0.72 0.46; 1.14 0.16 0.70 0.46; 1.07 0.10 1.12 0.77; 1.64 0.55 Test for parallel curves between TTM groups 0.20
95% CI
p-value
<0.001
Data from the repeated measures mixed model for comparison of each sample between TTM-groups with corresponding p-values and a comparison of progression over time between TTM-groups with p-values from a test for parallel curves also from the repeated measures mixed model. TTM24 = Targeted Temperature Management for 24 h. TTM48 = Targeted Temperature Management for 48 h. Data are presented as medians with confidence intervals (95% CI). “n” = number of samples.
Fig. 2. NSE & S-100b time course. Plots of neuron-specific enolase (NSE) and protein S–100 B over the first 3 days after cardiac arrest. The higher two plots show NSE and S-100b levels between TTM groups, and the lower two plots depict NSE and S-100b between outcome groups. We found no significant differences between TTM groups in levels of NSE on progression over time (p = 0.20). In levels of S-100b we found a difference between TTM-groups on progression over time (p < 0.001). Significant differences between outcome groups were found at t24, t48 and t72, but not at admission. Data are presented as medians with 95% confidence intervals (CI). TTM24 = targeted temperature management for 24 h (standard duration). TTM48 = targeted temperature management for 48 h (prolonged duration). Admission = sample at admission, t24 = sample at 24 h after reaching target temperature, t48 = sample at 48 h after reaching target temperature and t72 = sample at 72 h after reaching target temperature. P-values below 0.05 are marked with *.
1.48 (0.88; 2.87) at admission (p = 0.15), 0.09 (0.07; 0.11) versus 0.23 (0.19; 0.39) at t24 (p = 0.02), 0.08 (0.07; 0.09) versus 0.18 (0.15; 0.33) at t48 (p = 0.01) and 0.07 (0.06; 0.08) versus 0.13 (0.09; 0.23) at t72 (p = 0.03). Comparisons of biomarker data of
good and poor outcome groups according to the TTM duration were not performed due to small sample size in the poor outcome groups.
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Fig. 3. ROC-curves. Receiver operating characteristic curves (ROC-curves) for NSE and S-100b for each sample time-point with area under the curve (AUC) and 95% confidence intervals (95% CI). Sample time-points are: Admission = sample taken immediately after patient admission to the hospital, t24 = 24 h after reaching target temperature, t48 = 48 h after reaching target temperature, t72 = 72 h after reaching target temperature.
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Table 3 NSE and S-100b cut-off values. Pooled samples
Admission sample
t24 sample
t48 sample
t72 sample
Changes over time admission to t24
t24 to t48
t48 to t72
NSE
S-100b
cut-off (ng/ml)
Sensitivity
95% CI
Specificity
95% CI
cut-off (ng/ml)
Sensitivity
5% FPR 3% FPR 1% FPR 0% FPR 5% FPR 3% FPR 1% FPR 0% FPR 5% FPR 3% FPR 1% FPR 0% FPR 5% FPR 3% FPR 1% FPR 0% FPR
52.4 69.04 123.3 141.6 29.87 31.43 32.01 40.55 20.9 29.75 37.78 45.12 24.26 31.05 40.63 47.17
0.07 0.07 0.00 0.00 0.26 0.26 0.26 0.23 0.48 0.38 0.31 0.31 0.56 0.52 0.41 0.41
0.01–0.22 0.01–0.22 0–0.12 0–0.12 0.12–0.43 0.12–0.43 0.1–0.4 0.08–0.37 0.29–0.67 0–0.18 0.15–0.51 0.13–0.47 0.35–0.75 0.29–0.68 0.22–0.61 0.19–0.58
0.96 0.97 0.97 1.00 0.95 0.97 0.99 1.00 0.95 0.97 0.99 1.00 0.95 0.97 0.99 1.00
0.88–0.99 0.9–1 0.9–1 0.92–1 0.87–0.99 0.91–1 0.93–1 0.95–1 0.89–0.99 0.95–1 0.95–1 0.95–1 0.87–0.98 0.9–1 0.93–1 0.95–1
4.32 5.27 5.46 16.6 0.27 0.50 0.92 1.05 0.22 0.23 0.34 0.95 0.22 0.24 0.3 0.72
0.19 0.16 0.16 0.03 0.43 0.31 0.23 0.23 0.43 0.43 0.33 0.17 0.36 0.32 0.25 0.11
95% CI 0.07–0.37 0.05–0.34 0.05–0.34 0–0.17 0.26–0.61 0.17–0.49 0.1–0.4 0.08–0.37 0.25–0.63 0.23–0.59 0.15–0.49 0.04–0.31 0.16–0.52 0.16–0.52 0.11–0.45 0.01–0.24
Specificity 0.96 0.97 0.99 1.00 0.95 0.97 0.99 1.00 0.95 0.97 0.99 1.00 0.95 0.97 0.99 1.00
95% CI 0.88–0.99 0.92–1 0.92–1 0.95–1 0.89–0.99 0.91–1 0.93–1 0.95–1 0.89–0.99 0.91–1 0.93–1 0.95–1 0.87–0.99 0.91–1 0.93–1 0.95–1
5% FPR 3% FPR 1% FPR 0% FPR 5% FPR 3% FPR 1% FPR 0% FPR 5% FPR 3% FPR 1% FPR 0% FPR
5.00 9.08 9.69 12.37 8.32 10.69 15.70 39.09 6.98 13.66 18.17 23.18
0.41 0.31 0.31 0.31 0.46 0.43 0.39 0.18 0.31 0.23 0.19 0.15
0.24–0.61 0.15–0.51 0.15–0.51 0.15–0.51 0.28–0.66 0.24–0.63 0.22–0.59 0.06–0.37 0.14–0.52 0.09–0.44 0.07–0.39 0.04–0.35
0.95 0.97 0.99 1.00 0.95 0.97 0.99 1.00 0.95 0.97 0.99 1.00
0.88–0.99 0.92–1 0.92–1 0.95–1 0.87–0.99 0.91–1 0.93–1 0.95–1 0.88–0.99 0.9–1 0.92–1 0.95–1
−0.047 –0.014 –0.005 0.03 0.081 0.121 0.208 0.323 0.056 0.061 0.081 0.118
0.30 0.30 0.30 0.30 0.10 0.10 0.10 0.10 0.11 0.11 0.11 0.11
0.15–0.49 0.15–0.49 0.15–0.49 0.15–0.49 0.02–0.27 0.02–0.27 0.02–0.27 0.02–0.27 0.02–0.28 0.02–0.28 0.02–0.28 0.02–0.28
0.97 0.97 0.99 1.00 0.95 0.97 1.00 1.00 0.95 0.99 0.99 1.00
0.9–1 0.9–1 0.92–1 0.95–1 0.87–0.99 0.91–1 0.95–1 0.95–1 0.87–0.99 0.93–1 0.93–1 0.95–1
Cut–off levels for all samples (pooled) at the false positive rates (FPR) of 0%, 1%, 3% and 5% with their corresponding specificity, sensitivity and their 95% confidence intervals (CI). Upper part of the table shows the four specific sample time-points; admission sample, t24 sample: 24 h after the patient reached target temperature (TT), t48 sample: 48 h after reaching TT and t72 sample: 72 h after reaching TT. The lower part of the table shows cut-offs for serum level changes over time from one sample to the next.
We found an association between the neurological outcome and NSE level changes from admission to t24 (p = 0.003), and again from t24 to t48 (p = 0.02). Changes in S-100b over time showed no significant association with patient outcomes (p-values > 0.21). The biomarker levels decreased significantly and consistently in the good-outcome group between all the four sample points, in both NSE and S-100b. The cut-off values for prediction of outcome on the pooled patient population are presented in Table 3 for the false positive rates (FPR) of 5, 3, 1, and 0 both at each sample time-point as well as for changes over time from one sample time-point to the next. The predictive performance of NSE and S-100b was assessed using ROC-analyses (Fig. 3). NSE predicted prognosis optimally at t48 and t72. S-100b predicted prognosis best at t24 and t48. We observed no significant difference in AUROC at the specific sample time-points or in the progression over time between the prolonged and standard duration of TTM (data not shown). Discussion In the present study, we found no statistically significant attenuating effect of 48 h of TTM on NSE and S-100b levels, as compared to the standard 24-h TTM. We found that higher NSE and S-100b levels predicted poor neurological outcome at the specific time points t24, t48, and t72. Likewise, a rise in NSE levels from t24 to t48 predicted a poor neurological outcome. Prolonged TTM did not alter the prognostic performance of the two biomarkers. A relatively small Finnish study [12] randomised patients to TTM at 33 ◦ C versus normothermia, and found that NSE levels were lower in the TTM group treated with 33 ◦ C, suggesting the possibility of a less delayed neuronal death in patients treated with TTM at 33 ◦ C. The influence of target temperatures of 33 vs 36 ◦ C
on the release and prognostic capabilities of NSE and S100b was investigated by Stammet et al. in two large studies [7,8], finding no difference in the biomarker levels between the two temperature groups. This indicates that the release of these biomarkers following a cardiac arrest is quite unaffected by the temperature range, and with the results of the present study in mind, maybe also unaffected by the duration of cooling. The levels of the two biomarkers upon admission were markedly higher than at all the other time-points, but the variability was high, suggesting limited prognostic capabilities in these early samples per se, in line with the findings from other studies [13]. However, in NSE, we saw an association between the outcome and the changes in the serum levels from admission to t24 (p = 0.003), indicating that the analysis of progression over time is a valuable prognostic parameter that requires an admission sample. According to our ROC data, prognostication using NSE was best at t48 and t72 (Fig. 3). This has also been shown by both Stammet et al. [8] and Vondrakova et al. [14]. In our results, S-100b performed alike at both t24 and t48, wherein the largest trial on S-100b after cardiac arrest by Stammet et al. [7] reported that S-100b at t24 was better at prognostication, as compared to t48. We found a relationship between an increase in the NSE levels and poor outcome, in line with the Stammet study [7] (Table 3). These results are in consonance with the current recommendations from the European Resuscitation Council (ERC) stating that increasing levels of NSE may have an additional prognostic value [5]. In our study, NSE was superior to S-100b in its predictive properties, owing to the added significant relation between changes in the serum levels over time and the outcome, as compared to S-100b where this relationship was absent. Several studies have suggested that the NSE levels at 48 h after ROSC have the best discriminative value for a poor outcome
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[8,15–17], as compared to NSE collected at earlier time-points, as was also found in our results. However, the ERC’s most recent guidelines on prognostication from 2015 have abandoned the idea of proposing a general cut-off point, with a false positive rate (FPR) of 0% due to the incomplete knowledge on biomarker kinetics, and variation in the results caused by different analytical methods. Furthermore, larger trials will by nature have more outliers. By accepting cut-offs with FPR’s of up to 5% in a multimodal approach, physicians will have more useful information, and a more multifaceted approach to prognostication on the individual patient. Indeed, recommendations now focus on the importance of multimodal approaches to prognostication, including cut-offs with low FPR’s from 0 to 5% [5]. Therefore, biomarkers remain important parameters to support the more robust prognosticators, such as the absence of a cortical N20 response in SSEP and the absence of corneal and pupillary reflexes 72 h after CA [5]. Biomarker sampling should be commenced upon admission and continued during the first days after the cardiac arrest. Multiple sampling reduces the risk of false positive results, as caused by haemolysis or extra cerebral sources of NSE and S-100b, and provides the opportunity to assess progression over time for additional prognostic value. Cut-off values may still be useful in the multimodal approach to prognostication, in a setting where thresholds have been established locally but they cannot function as stand-alone prognostic parameters. Prognostication by biomarkers is a very accessible and inexpensive supplement to EEG, SSEP, and CT/MRI. Biomarkers provide quantitative results and do not require specialist interpretation or relocation of critically ill and unstable patients.
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Conclusion Prolonged targeted temperature management for 48 h at 33 ◦ C after an out-of-hospital cardiac arrest did not attenuate the levels of NSE and S-100b, as compared to the standard 24-h TTM, nor did it affect the changes over time at a clinically relevant level. The NSE and S-100b levels at all time-points, except at admission, as well as daily changes over time up until 48 h after reaching target temperature, predicted outcome at 6 months in both standard 24-h TTM, and prolonged 48-h TTM. This suggests that NSE and S-100b are safe to be used as prognosticators during prolonged TTM. Conflicts of interest Christophe H. V. Duez received funding for research in neuroprognostication from the private foundations the Viggo and Helene Bruun Foundation, the Lily Benthine Lunds Foundation of 1st of June 1978, the Director Jacob Madsen & Wife Olga Madsen Foundation and the Grocer A. V. Lykfeldt and Wife Foundation. The foundations had no influence on the study design, execution, analysis or interpretation of the data. Co-authors had nothing to disclose. Acknowledgement We wish to thank the staff at the ICUs in Stavanger University Hospital and Aarhus University Hospital. References
Strengths and limitations In our assessment of the possible impact of prolonged cooling on biomarker levels, the t48 and t72 samples were of specific interest, since treatment of patients was identical up to t24. The possible effects of prolonged TTM would, therefore, not be seen before t48. We saw a tendency towards differing biomarker levels between TTM24 and TTM48 in our NSE admission samples, suggesting a skewness with regards to the severity of the initial ischemic insult. Furthermore, we found a near-significant difference between the two TTM-groups in terms of the biomarker change from admission to t24, which was possibly a consequence of the differences found in the admission sample. These are probably random findings, since no differences were found in the baseline characteristics (Table 1) and the same skewness was not present in our S-100b admission samples. All samples were gathered and analysed at one particular laboratory in Denmark, in order to minimise the variation between the analytical methods, which are reported to vary by up to 36% between laboratories [18]. The samples were analysed in two batches, to take the time-limit recommendations for storing the samples into account. The biomarker results were blinded from the treating physicians, minimising the risk of a “self-fulfilling prophecy”. Furthermore, a guide to standardised prognostication and withdrawal of care was used in the two participating centres, improving the validity of our results. The primary weaknesses of our study were the small sample size and the missed inclusions. The difference in the number of percutaneous coronary interventions, performed between the missed inclusions and included patients (Table 1) could be due to early deaths in the missed inclusion group, albeit no difference in the days to death between the missing and included patients was found. The reason for the difference in the performed pci was probably a random finding due to our small sample size.
[1]. Grasner JT, Bottiger BW, Bossaert L. EuReCa ONE − ONE month − ONE europe − ONE goal. Resuscitation 2014;85:1307–8. [2]. Bernard SA, Gray TW, Buist MD, Jones BM, Silvester W, Gutteridge G, et al. Treatment of comatose survivors of out-of-hospital cardiac arrest with induced hypothermia. N Engl J Med 2002;346:557–63. [3]. Mild therapeutic hypothermia to improve the neurologic outcome after cardiac arrest. N Engl J Med 2002;346:549–56. [4]. Nielsen N, Wetterslev J, Cronberg T, Erlinge D, Gasche Y, Hassager C, et al. Targeted temperature management at 33 degrees C versus 36 degrees C after cardiac arrest. N Engl J Med 2013;369:2197–206. [5]. Nolan JP, Soar J, Cariou A, Cronberg T, Moulaert VR, Deakin CD, et al. European resuscitation council and european society of intensive care medicine guidelines for post-resuscitation care 2015: section 5 of the european resuscitation council guidelines for resuscitation 2015. Resuscitation 2015;95:202–22. [6]. Kirkegaard H, Soreide E, de Haas I, Pettila V, Taccone FS, Arus U, et al. Targeted temperature management for 48 vs 24 hours and neurologic outcome after outof-Hospital cardiac arrest: a randomized clinical trial. JAMA 2017;318:341–50. [7]. Stammet P, Dankiewicz J, Nielsen N, Fays F, Collignon O, Hassager C, et al. Protein S100 as outcome predictor after out-of-hospital cardiac arrest and targeted temperature management at 33 degrees C and 36 degrees C. Crit Care 2017;21:153. [8]. Stammet P, Collignon O, Hassager C, Wise MP, Hovdenes J, Aneman A, et al. Neuron-Specific enolase as a predictor of death or poor neurological outcome after out-of-Hospital cardiac arrest and targeted temperature management at 33 degrees c and 36 degrees C. J Am Coll Cardiol 2015;65:2104–14. [9]. Kirkegaard H, Rasmussen BS, de Haas I, Nielsen JF, Ilkjaer S, Kaltoft A, et al. Time-differentiated target temperature management after out-of-hospital cardiac arrest: a multicentre, randomised, parallel-group, assessor-blinded clinical trial (the TTH48 trial): study protocol for a randomised controlled trial. Trials 2016;17:228. [10]. Cummins RO, Chamberlain DA, Abramson NS, Allen M, Baskett PJ, Becker L, et al. Recommended guidelines for uniform reporting of data from out-of-hospital cardiac arrest: the Utstein Style A statement for health professionals from a task force of the American Heart Association, the European Resuscitation Council, the Heart and Stroke Foundation of Canada, and the Australian Resuscitation Council. Circulation 1991;84:960–75. [11]. A randomized clinical study of a calcium-entry blocker (lidoflazine) in the treatment of comatose survivors of cardiac arrest. Brain Resuscitation Clinical Trial II Study Group. N Engl J Med 1991;324:1225–31. [12]. Tiainen M, Roine RO, Pettila V, Takkunen O. Serum neuron-specific enolase and S-100 B protein in cardiac arrest patients treated with hypothermia. Stroke 2003;34:2881–6. [13]. Calderon LM, Guyette FX, Doshi AA, Callaway CW, Rittenberger JC. Combining NSE and S100 B with clinical examination findings to predict survival after resuscitation from cardiac arrest. Resuscitation 2014;85:1025–9.
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[14]. Vondrakova D, Kruger A, Janotka M, Malek F, Dudkova V, Neuzil P, et al. Association of neuron-specific enolase values with outcomes in cardiac arrest survivors is dependent on the time of sample collection. Crit Care 2017;21:172. [15]. Oksanen T, Tiainen M, Skrifvars MB, Varpula T, Kuitunen A, Castren M, et al. Predictive power of serum NSE and OHCA score regarding 6-month neurologic outcome after out-of-hospital ventricular fibrillation and therapeutic hypothermia. Resuscitation 2009;80:165–70. [16]. Bouwes A, Binnekade JM, Kuiper MA, Bosch FH, Zandstra DF, Toornvliet AC, et al. Prognosis of coma after therapeutic hypothermia: a prospective cohort study. Ann Neurol 2012;71:206–12.
[17]. Lee BK, Jeung KW, Lee HY, Jung YH, Lee DH. Combining brain computed tomography and serum neuron specific enolase improves the prognostic performance compared to either alone in comatose cardiac arrest survivors treated with therapeutic hypothermia. Resuscitation 2013;84:1387–92. [18]. Rundgren M, Cronberg T, Friberg H, Isaksson A. Serum neuron specific enolase − impact of storage and measuring method. BMC Res Notes 2014;7:726.
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Clinical paper
Neuron-specific enolase and S-100b in prolonged targeted temperature management after cardiac arrest: A randomised study夽 Christophe Henri Valdemar Duez a,b,∗ , Anders Morten Grejs a,b , Anni Nørgaard Jeppesen a,b , Anne Dilani Schrøder c , Eldar Søreide d,e , Jørgen Feldbæk Nielsen f , Hans Kirkegaard b a
Department of Anaesthesiology and Intensive Care Medicine, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus N, Denmark Research Centre for Emergency Medicine, Aarhus University Hospital, Nørrebrogade 44, Building 1B, 1st floor, 8000, Aarhus C, Denmark c Department of Clinical Biochemistry, Aarhus University Hospital, Palle Juul-Jensens Boulevard 99, 8200, Aarhus N, Denmark d Critical Care and Anaesthesiology Research Group, Stavanger University Hospital, Norway e Department of Clinical Medicine, University of Bergen, Bergen, Norway f Hammel Neurorehabilitation and Research Centre (HNRC), Denmark b
a r t i c l e
i n f o
Article history: Received 7 August 2017 Received in revised form 14 November 2017 Accepted 19 November 2017 Keywords: Neuron-specific enolase S-100b Prognostication Prolonged targeted temperature management Cardiac arrest Therapeutic hypothermia
a b s t r a c t Background: We aimed to investigate the impact of prolonged targeted temperature management (TTM) in cardiac arrest patients on release of serum levels of NSE and S-100b and their prognostic performances. Methods: This is a substudy of the Targeted Temperature Management for 24 vs 48 h trial. NSE and S-100b levels were analysed retrospectively in serum samples collected upon admission, at 24, 48, and 72 h after reaching the target temperature of 33 ± 1 ◦ C. The primary outcome was biomarker serum concentrations and secondary outcome was the cerebral performance category score after 6 months. Results: 115 patients from two centres were analysed. NSE and S-100b levels did not differ between TTM groups at any single time-point. Poor outcome patients had higher biomarker levels at 24, 48, and 72 h: NSE: 9.73 (7.2; 10.9) versus 20.40 (12.7; 27.2), 8.86 (6.6; 9.6) versus 17.47 (11.1; 37.3) and 6.23 (5.3; 8.5) versus 31.05 (12.8; 52.5) respectively and S-100b: 0.09 (0.07; 0.11) versus 0.23 (0.19; 0.39), 0.08 (0.07; 0.09) versus 0.18 (0.15; 0.33) and 0.07 (0.06; 0.08) versus 0.13 (0.09; 0.23). The daily changes in NSE from admission to Day 2 after the cardiac arrest (CA) were also related to the outcome (p = 0.003 and p = 0.02). The best prediction of outcome was found at 72 h for NSE and at 24 h as well as 48 h for S100b. Conclusions: No clinically relevant differences were found in the levels of NSE or S-100b between standard and prolonged TTM. Prognostic reliability of NSE and S-100b was unaltered by prolonged TTM. © 2017 Published by Elsevier Ireland Ltd.
Introduction Out-of-hospital cardiac arrest (OHCA) affects an estimated 400,000 people in Europe each year [1], and with a mere 10% survival rate, it is a major cause of death. Two landmark studies from 2002 [2,3] demonstrated that targeted temperature management (TTM) at 33 ◦ C for 12–24 h improved the neurological outcome and survival in comatose OHCA patients admitted to the intensive care unit (ICU). Consequently, TTM at 33 ◦ for 24 h became the standard
夽 A Spanish translated version of the abstract of this article appears as Appendix in the final online version at https://doi.org/10.1016/j.resuscitation.2017.11.052 ∗ Corresponding author at: Intensive Care Research Unit/Research Centre for Emergency Medicine Palle Juul Jensens Boulevard 99, Aarhus University Hospital, DK-8200, Aarhus N, Denmark. E-mail address: [email protected] (C.H.V. Duez). https://doi.org/10.1016/j.resuscitation.2017.11.052 0300-9572/© 2017 Published by Elsevier Ireland Ltd.
treatment in post-cardiac arrest therapy worldwide, albeit with a low level of evidence. The TTM-trial from 2013 [4], randomising 950 OHCA patients, demonstrated that there was no difference in the neurological outcome, whether the patients were cooled to 33 or 36 ◦ C. As a result, the most recent guidelines now recommend TTM at 32–36 ◦ C for at least 24 h in OHCA patients [5]. Besides the optimal TTM temperature, duration of TTM is another big question within post-resuscitation care research. In search of an answer to this question, a study including 355 OHCA patients [6] reported no difference in the neurological outcome of prolonged TTM for 48 h versus standard duration of TTM for 24 h. The introduction of TTM changed the reliability of the known prognosticators, and the importance of further investigations on prognosticators in this new setting is therefore important to secure safety in prognostication. The blood concentration of the two biomarkers, neuron-specific enolase (NSE) and protein S-100b, are
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associated with the neurological outcome and play an important role in prognostication due to their almost universal accessibility and low costs. The two largest studies on NSE and S-100b levels in OHCA patients to date [7,8] reported that an intervention in the 33–36 ◦ C span did not affect the levels of the two biomarkers to a clinically relevant degree, albeit the levels of S-100b were higher in patients treated with TTM to 33 ◦ C at two of the three sample time-points. The aim of the present study was to investigate whether prolonged TTM would reduce NSE and S-100b serum levels or cause changes in the biomarker levels over time. Furthermore, we wanted to explore the prognostic performance of the two biomarkers at specific time-points as well as their progression over time from one sample to the next. We hypothesised that prolonged TTM for 48 h would reduce the serum levels of NSE and S-100b, as compared to the standard 24-h duration of TTM. Methods Patients All the patients included in the present study were a subset of the patients (n = 355) included in the randomised multicentre study, “Targeted Temperature Management for 48 vs 24 h and Neurologic Outcome After Out-of-Hospital Cardiac Arrest: A Randomized Clinical Trial” (the TTH48 trial) [6]. TTH48 compares the effect on the neurological outcomes of 24 vs. 48 h of TTM at 33 ± 1 ◦ C. In the present prospective study, a total of 159 patients were enrolled in the ICUs at Aarhus University Hospital, Denmark, and Stavanger University Hospital, Norway. The inclusion criteria were the following: OHCA with a presumed cardiac origin, Glasgow Coma Scale below 8, sustained spontaneous circulation after resuscitation (no need for cardiac compressions for 20 min and clinical signs of circulation), aged between 18 and 80 years. The exclusion criteria were as follows: estimated time from collapse to return of spontaneous circulation (ROSC) of more than 60 min, terminal disease, severe coagulopathy, unwitnessed OHCA with asystole as first rhythm, time from cardiac arrest to the initiation of cooling of more than 240 min, pregnancy, previous neurological disease with cognitive impairment, persistent cardiogenic shock, systolic blood pressure below 80 mmHg despite vasoactive treatment and/or aortic balloon pump intervention, suspected or confirmed acute intracerebral bleeding/acute stroke, acute coronary artery bypass surgery, or lack of consent [9]. All the patients were treated either with TTM for 48 h (TTM48) or standard duration TTM for 24-h (TTM24). Either surface or intravascular feedback cooling systems were employed to maintain target temperature (TT). The rewarming rate was 0.5 ◦ C h−1 . The body core temperature was continuously monitored in the urinary bladder throughout TTM. The patients were sedated with intravenous infusions of propofol/midazolam and remifentanil/fentanyl until normothermia was reached. Clinical data were collected using the patients’ medical records and the patient data management systems. Prehospital cardiac arrest data were collected according to the Utstein guidelines [10]. The study was approved by the Danish Data Protection Agency and the Central Denmark Region Committees on Health Research Ethics (case number 20110022) and the Regional Ethics Committee of Western Norway (ref 2013/1486). Outcome measure The primary outcome measure was the serum concentrations of NSE and S-100b. The levels of NSE and S-100b were assessed at four time-points. The first blood sample was drawn upon patient
admission while the second sample was drawn 24 h (t24) after the patient reached the TT. The time was measured from the moment when the core temperature breached the 34 ◦ C threshold. The third sample was drawn at 48 h (t48) after reaching the TT and the fourth sample at 72 h after obtaining the TT (t72). The secondary outcome was the cerebral performance categories (CPC) [10,11] at 6 months. The CPC score was assessed by a researcher blinded to the intervention, either by a phone interview at Aarhus or by a face-to-face interview at Stavanger. The CPC score is defined as follows: CPC 1: no neurological deficit, CPC 2: mild to moderate dysfunction, CPC 3: severe dysfunction, CPC 4: coma, and CPC 5: death. The outcome was dichotomised so that a CPC score of 1–2 was considered a good neurological outcome while a CPC score of 3–5 was considered a poor outcome. Blood samples Blood samples for the NSE and S100b analyses were centrifuged within an hour after the collection and the serum was stored at −80 C◦ until analysis. Samples were analysed a posteriori at a single core lab in two batches, using the Cobas E601 system with an electrochemiluminescence immunoassay (Roche Diagnostics, Mannheim, Germany). Measurement ranges were 0.3–740 g/l for NSE and 0.02–39 g/l for S-100b. The level of hemolysis was assessed through a fotometric measurement of the absorbance at two different wavelengths (570 nanometers (nm) and 600 nm). Statistical analysis The baseline characteristics were presented as medians and interquartile ranges for continuous data and as counts and percentages for categorical variables. They were compared between the TTM groups using the Mann-Whitney U test. The biomarker levels were presented as medians with 95% confidence intervals (CI). Sensitivity and specificity were calculated at different cut-off values at the specific sample time-points and for changes over time using a nonparametric ROC analysis, reported as percentages with 95% CI. A repeated measures mixed model was employed to test for the differences in the biomarker levels between the two TTM groups at each sample time-point. The same process was followed to test for progression over time in the serum levels of the biomarkers through all four samples using a test for parallel curves. A multiple logistic regression adjusted for minutes to ROSC, primary rhythm (shockable or non-shockable), and age was used to test for a relationship between good (CPC 1–2) and poor neurologic outcomes (CPC 3–5) at 6 months for each of the four samples (admission, t24, t48, and t72) and for changes in serum levels from one sample to the next. Multiple imputation to adjust for the missing samples was not employed. The prognostic performance was evaluated by the unadjusted areas under the receiver operating characteristic curves (AUROCs) at each sample time and for changes in the serum levels over time. A power calculation was not performed, since we aimed to include as many patients as possible from the main TTH48-trial. Statistical analysis was performed using STATA 13.1 (StataCorp LP, TX, USA). A p-value < 0.05 was considered to indicate statistical significance. Results A total of 159 patients treated with TTM for 24 or 48 h at 33 ◦ C were enrolled in the TTH48 trial during the study period, at both Aarhus and Stavanger. Blood samples were collected from 128 of these patients; 115 were included in the final statistical analysis (Fig. 1). At the 6-month follow-up, 79 patients (69%) had a good neurological outcome (CPC score 1 or 2) while 36 had a poor neurological outcome (CPC score 3–5). No significant differences were
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Fig. 1. Study flowchart. a) Presentation of patients enrolled in the main TTH48 trial and in this substudy. b): Sample flowchart presenting reasons for missing and excluded samples. TTM24 = Targeted Temperature Management for 24 h. TTM48 = Targeted Temperature Management for 48 h. CPC = cerebral performance categories outcome scale.
Table 1 Baseline characteristics. pooled (n)
Patients Age, years (median and IQR) Male Bystander CPR performed Primary shockable rhythm Time to ROSC, minutes (median and IQR) PCI performed previous AMI Diabetes Mellitus
%
TTM24 (n)
115 61 (53–69) 98 85% 91 79% 98 85% 20 (15–31) 43 21 20
37% 18% 17%
%
56 61 (53–69) 49 44 47 20 (14–32)
49%
21 11 9
18% 10% 8%
88% 79% 84%
TTM48 (n)
%
59 61 (53–69) 49 47 51 21 (16–28)
51% 83% 80% 86%
22 10 11
19% 9% 10%
p-value
Missed inclusion n
% 28%
0.81 0.60 0.75 0.80 0.77
44 65 (53–72) 38 39 35 24 (17–30)
p-value
86% 89% 80%
0.28 0.65 0.37 0.77 0.62
0.63 0.68 0.72
26 6 8
59% 14% 18%
<0.001 0.63 0.81
TTM24 = Targeted Temperature Management for 24 h. TTM48 = Targeted Temperature Management for 48 h. Values are number (n) or median and percent of total (%). IQR = inter quartile range, ROSC = return of spontaneous circulation. CPR = cardiopulmonary resuscitation, PCI = percutaneous coronary intervention, AMI = acute myocardial infarction. P-values are the results of Mann-Whitney U test between TTM groups. The “Missed inclusion” columns compares the 44 patients missed for inclusion with the 115 included patients.
found in the baseline characteristics (Table 1) or in the neurological outcome measured by CPC between the two TTM groups (p = 0.55). No significant differences were found between the 44 missed inclusions and the 115 analysed patients in baseline characteristics or neurological outcome (p = 0.97), except for the number of performed percutaneous coronary interventions (Table 1). Biomarker levels in prolonged vs standard duration of TTM We found no difference between prolonged and standard duration of TTM at any sample time-point in NSE or S-100b serum concentrations (Table 2). The levels of NSE and S-100b generally decreased over time, from admission to t72 with a marked decrease from admission to t24 (Fig. 2). The progression of NSE levels over
time was unaffected by the prolonged TTM (p = 0.20), but a difference between the TTM-groups was found for S-100b (p < 0.001). Prediction of neurological outcome by biomarker levels Since no difference in the biomarker levels between the two TTM groups in the present study could be demonstrated, the data for prognostication analyses were pooled. NSE and S-100b levels were higher in patients with poor outcome at all time-points (Fig. 2). For NSE, levels were 19.86 (16.8; 23.4) versus 24.40 (19.8; 30.0) at admission (p = 0.88), 9.73 (7.2; 10.9) versus 20.40 (12.7; 27.2) at t24 (p = 0.01), 8.86 (6.6; 9.6) versus 17.47 (11.1; 37.3) at t48 (p = 0.01) and 6.23 (5.3; 8.5) versus 31.05 (12.8; 52.5) at t72 (p = 0.001). For S-100b levels were: 0.83 (0.63; 1.10) versus
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Table 2 Repeated measures mixed model analysis. Biomarker levels between TTM groups at each sample time-point TTM24 Estimated Median (g/l) NSE arrival NSE 24 h (t24) NSE 48 h (t48) NSE 72 h (t72) S100b arrival S100b 24 h (t24) S100b 48 h (t48) S100b 72 h (t72)
NSE arr-t24 NSE t24−t48 NSE t48-t72 S100b arr-t24 S100b t24-t48 S100b t48-t72
Mixed model analysis
TTM48 95% CI
n
Estimated Median (g/l)
17.8 14.4; 21.2 49 22.8 12.4 9.5; 15.4 55 11.4 12.3 8.6; 16.1 50 10.0 7.6; 14.4 11.0 48 9.5 0.86 0.59; 1.14 49 0.93 0.17 0.12; 0.23 55 0.13 0.15 0.11; 0.20 51 0.11 0.09 0.07; 0.12 49 0.1 Median change in biomarker levels from sample to sample between TTM groups −6.19 −0.26 −3.04 −0.57 −0.01 −0.04
−9.2; 2.0 −2.3; 2.6 −4.2; 0.78 −0.94; −0.24 −0.04; 0.002 −0.05; −0.02
48 49 45 48 50 47
−9.00 −1.18 −0.15 −0.74 −0.02 0.003
95% CI
n
exp(b)
18.6; 27.0 8.8; 14.0 7.1; 13.0 6.7; 12.4 0.64; 1.21 0.09; 0.17 0.08; 0.14 0.08; 0.13
51 58 55 52 53 58 55 54
−12.8; −6.3 −2.7; 0.26 −1.0; 0.74 −1.2; −0.47 −0.03; −0.01 −0.003; 0.01
50 54 52 52 54 54
1.28 0.98; 1.67 0.07 0.92 0.66; 1.27 0.60 0.81 0.53; 1.24 0.34 0.87 0.56; 1.34 0.53 1.07 0.69; 1.68 0.75 0.72 0.46; 1.14 0.16 0.70 0.46; 1.07 0.10 1.12 0.77; 1.64 0.55 Test for parallel curves between TTM groups 0.20
95% CI
p-value
<0.001
Data from the repeated measures mixed model for comparison of each sample between TTM-groups with corresponding p-values and a comparison of progression over time between TTM-groups with p-values from a test for parallel curves also from the repeated measures mixed model. TTM24 = Targeted Temperature Management for 24 h. TTM48 = Targeted Temperature Management for 48 h. Data are presented as medians with confidence intervals (95% CI). “n” = number of samples.
Fig. 2. NSE & S-100b time course. Plots of neuron-specific enolase (NSE) and protein S–100 B over the first 3 days after cardiac arrest. The higher two plots show NSE and S-100b levels between TTM groups, and the lower two plots depict NSE and S-100b between outcome groups. We found no significant differences between TTM groups in levels of NSE on progression over time (p = 0.20). In levels of S-100b we found a difference between TTM-groups on progression over time (p < 0.001). Significant differences between outcome groups were found at t24, t48 and t72, but not at admission. Data are presented as medians with 95% confidence intervals (CI). TTM24 = targeted temperature management for 24 h (standard duration). TTM48 = targeted temperature management for 48 h (prolonged duration). Admission = sample at admission, t24 = sample at 24 h after reaching target temperature, t48 = sample at 48 h after reaching target temperature and t72 = sample at 72 h after reaching target temperature. P-values below 0.05 are marked with *.
1.48 (0.88; 2.87) at admission (p = 0.15), 0.09 (0.07; 0.11) versus 0.23 (0.19; 0.39) at t24 (p = 0.02), 0.08 (0.07; 0.09) versus 0.18 (0.15; 0.33) at t48 (p = 0.01) and 0.07 (0.06; 0.08) versus 0.13 (0.09; 0.23) at t72 (p = 0.03). Comparisons of biomarker data of
good and poor outcome groups according to the TTM duration were not performed due to small sample size in the poor outcome groups.
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Fig. 3. ROC-curves. Receiver operating characteristic curves (ROC-curves) for NSE and S-100b for each sample time-point with area under the curve (AUC) and 95% confidence intervals (95% CI). Sample time-points are: Admission = sample taken immediately after patient admission to the hospital, t24 = 24 h after reaching target temperature, t48 = 48 h after reaching target temperature, t72 = 72 h after reaching target temperature.
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Table 3 NSE and S-100b cut-off values. Pooled samples
Admission sample
t24 sample
t48 sample
t72 sample
Changes over time admission to t24
t24 to t48
t48 to t72
NSE
S-100b
cut-off (ng/ml)
Sensitivity
95% CI
Specificity
95% CI
cut-off (ng/ml)
Sensitivity
5% FPR 3% FPR 1% FPR 0% FPR 5% FPR 3% FPR 1% FPR 0% FPR 5% FPR 3% FPR 1% FPR 0% FPR 5% FPR 3% FPR 1% FPR 0% FPR
52.4 69.04 123.3 141.6 29.87 31.43 32.01 40.55 20.9 29.75 37.78 45.12 24.26 31.05 40.63 47.17
0.07 0.07 0.00 0.00 0.26 0.26 0.26 0.23 0.48 0.38 0.31 0.31 0.56 0.52 0.41 0.41
0.01–0.22 0.01–0.22 0–0.12 0–0.12 0.12–0.43 0.12–0.43 0.1–0.4 0.08–0.37 0.29–0.67 0–0.18 0.15–0.51 0.13–0.47 0.35–0.75 0.29–0.68 0.22–0.61 0.19–0.58
0.96 0.97 0.97 1.00 0.95 0.97 0.99 1.00 0.95 0.97 0.99 1.00 0.95 0.97 0.99 1.00
0.88–0.99 0.9–1 0.9–1 0.92–1 0.87–0.99 0.91–1 0.93–1 0.95–1 0.89–0.99 0.95–1 0.95–1 0.95–1 0.87–0.98 0.9–1 0.93–1 0.95–1
4.32 5.27 5.46 16.6 0.27 0.50 0.92 1.05 0.22 0.23 0.34 0.95 0.22 0.24 0.3 0.72
0.19 0.16 0.16 0.03 0.43 0.31 0.23 0.23 0.43 0.43 0.33 0.17 0.36 0.32 0.25 0.11
95% CI 0.07–0.37 0.05–0.34 0.05–0.34 0–0.17 0.26–0.61 0.17–0.49 0.1–0.4 0.08–0.37 0.25–0.63 0.23–0.59 0.15–0.49 0.04–0.31 0.16–0.52 0.16–0.52 0.11–0.45 0.01–0.24
Specificity 0.96 0.97 0.99 1.00 0.95 0.97 0.99 1.00 0.95 0.97 0.99 1.00 0.95 0.97 0.99 1.00
95% CI 0.88–0.99 0.92–1 0.92–1 0.95–1 0.89–0.99 0.91–1 0.93–1 0.95–1 0.89–0.99 0.91–1 0.93–1 0.95–1 0.87–0.99 0.91–1 0.93–1 0.95–1
5% FPR 3% FPR 1% FPR 0% FPR 5% FPR 3% FPR 1% FPR 0% FPR 5% FPR 3% FPR 1% FPR 0% FPR
5.00 9.08 9.69 12.37 8.32 10.69 15.70 39.09 6.98 13.66 18.17 23.18
0.41 0.31 0.31 0.31 0.46 0.43 0.39 0.18 0.31 0.23 0.19 0.15
0.24–0.61 0.15–0.51 0.15–0.51 0.15–0.51 0.28–0.66 0.24–0.63 0.22–0.59 0.06–0.37 0.14–0.52 0.09–0.44 0.07–0.39 0.04–0.35
0.95 0.97 0.99 1.00 0.95 0.97 0.99 1.00 0.95 0.97 0.99 1.00
0.88–0.99 0.92–1 0.92–1 0.95–1 0.87–0.99 0.91–1 0.93–1 0.95–1 0.88–0.99 0.9–1 0.92–1 0.95–1
−0.047 –0.014 –0.005 0.03 0.081 0.121 0.208 0.323 0.056 0.061 0.081 0.118
0.30 0.30 0.30 0.30 0.10 0.10 0.10 0.10 0.11 0.11 0.11 0.11
0.15–0.49 0.15–0.49 0.15–0.49 0.15–0.49 0.02–0.27 0.02–0.27 0.02–0.27 0.02–0.27 0.02–0.28 0.02–0.28 0.02–0.28 0.02–0.28
0.97 0.97 0.99 1.00 0.95 0.97 1.00 1.00 0.95 0.99 0.99 1.00
0.9–1 0.9–1 0.92–1 0.95–1 0.87–0.99 0.91–1 0.95–1 0.95–1 0.87–0.99 0.93–1 0.93–1 0.95–1
Cut–off levels for all samples (pooled) at the false positive rates (FPR) of 0%, 1%, 3% and 5% with their corresponding specificity, sensitivity and their 95% confidence intervals (CI). Upper part of the table shows the four specific sample time-points; admission sample, t24 sample: 24 h after the patient reached target temperature (TT), t48 sample: 48 h after reaching TT and t72 sample: 72 h after reaching TT. The lower part of the table shows cut-offs for serum level changes over time from one sample to the next.
We found an association between the neurological outcome and NSE level changes from admission to t24 (p = 0.003), and again from t24 to t48 (p = 0.02). Changes in S-100b over time showed no significant association with patient outcomes (p-values > 0.21). The biomarker levels decreased significantly and consistently in the good-outcome group between all the four sample points, in both NSE and S-100b. The cut-off values for prediction of outcome on the pooled patient population are presented in Table 3 for the false positive rates (FPR) of 5, 3, 1, and 0 both at each sample time-point as well as for changes over time from one sample time-point to the next. The predictive performance of NSE and S-100b was assessed using ROC-analyses (Fig. 3). NSE predicted prognosis optimally at t48 and t72. S-100b predicted prognosis best at t24 and t48. We observed no significant difference in AUROC at the specific sample time-points or in the progression over time between the prolonged and standard duration of TTM (data not shown). Discussion In the present study, we found no statistically significant attenuating effect of 48 h of TTM on NSE and S-100b levels, as compared to the standard 24-h TTM. We found that higher NSE and S-100b levels predicted poor neurological outcome at the specific time points t24, t48, and t72. Likewise, a rise in NSE levels from t24 to t48 predicted a poor neurological outcome. Prolonged TTM did not alter the prognostic performance of the two biomarkers. A relatively small Finnish study [12] randomised patients to TTM at 33 ◦ C versus normothermia, and found that NSE levels were lower in the TTM group treated with 33 ◦ C, suggesting the possibility of a less delayed neuronal death in patients treated with TTM at 33 ◦ C. The influence of target temperatures of 33 vs 36 ◦ C
on the release and prognostic capabilities of NSE and S100b was investigated by Stammet et al. in two large studies [7,8], finding no difference in the biomarker levels between the two temperature groups. This indicates that the release of these biomarkers following a cardiac arrest is quite unaffected by the temperature range, and with the results of the present study in mind, maybe also unaffected by the duration of cooling. The levels of the two biomarkers upon admission were markedly higher than at all the other time-points, but the variability was high, suggesting limited prognostic capabilities in these early samples per se, in line with the findings from other studies [13]. However, in NSE, we saw an association between the outcome and the changes in the serum levels from admission to t24 (p = 0.003), indicating that the analysis of progression over time is a valuable prognostic parameter that requires an admission sample. According to our ROC data, prognostication using NSE was best at t48 and t72 (Fig. 3). This has also been shown by both Stammet et al. [8] and Vondrakova et al. [14]. In our results, S-100b performed alike at both t24 and t48, wherein the largest trial on S-100b after cardiac arrest by Stammet et al. [7] reported that S-100b at t24 was better at prognostication, as compared to t48. We found a relationship between an increase in the NSE levels and poor outcome, in line with the Stammet study [7] (Table 3). These results are in consonance with the current recommendations from the European Resuscitation Council (ERC) stating that increasing levels of NSE may have an additional prognostic value [5]. In our study, NSE was superior to S-100b in its predictive properties, owing to the added significant relation between changes in the serum levels over time and the outcome, as compared to S-100b where this relationship was absent. Several studies have suggested that the NSE levels at 48 h after ROSC have the best discriminative value for a poor outcome
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[8,15–17], as compared to NSE collected at earlier time-points, as was also found in our results. However, the ERC’s most recent guidelines on prognostication from 2015 have abandoned the idea of proposing a general cut-off point, with a false positive rate (FPR) of 0% due to the incomplete knowledge on biomarker kinetics, and variation in the results caused by different analytical methods. Furthermore, larger trials will by nature have more outliers. By accepting cut-offs with FPR’s of up to 5% in a multimodal approach, physicians will have more useful information, and a more multifaceted approach to prognostication on the individual patient. Indeed, recommendations now focus on the importance of multimodal approaches to prognostication, including cut-offs with low FPR’s from 0 to 5% [5]. Therefore, biomarkers remain important parameters to support the more robust prognosticators, such as the absence of a cortical N20 response in SSEP and the absence of corneal and pupillary reflexes 72 h after CA [5]. Biomarker sampling should be commenced upon admission and continued during the first days after the cardiac arrest. Multiple sampling reduces the risk of false positive results, as caused by haemolysis or extra cerebral sources of NSE and S-100b, and provides the opportunity to assess progression over time for additional prognostic value. Cut-off values may still be useful in the multimodal approach to prognostication, in a setting where thresholds have been established locally but they cannot function as stand-alone prognostic parameters. Prognostication by biomarkers is a very accessible and inexpensive supplement to EEG, SSEP, and CT/MRI. Biomarkers provide quantitative results and do not require specialist interpretation or relocation of critically ill and unstable patients.
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Conclusion Prolonged targeted temperature management for 48 h at 33 ◦ C after an out-of-hospital cardiac arrest did not attenuate the levels of NSE and S-100b, as compared to the standard 24-h TTM, nor did it affect the changes over time at a clinically relevant level. The NSE and S-100b levels at all time-points, except at admission, as well as daily changes over time up until 48 h after reaching target temperature, predicted outcome at 6 months in both standard 24-h TTM, and prolonged 48-h TTM. This suggests that NSE and S-100b are safe to be used as prognosticators during prolonged TTM. Conflicts of interest Christophe H. V. Duez received funding for research in neuroprognostication from the private foundations the Viggo and Helene Bruun Foundation, the Lily Benthine Lunds Foundation of 1st of June 1978, the Director Jacob Madsen & Wife Olga Madsen Foundation and the Grocer A. V. Lykfeldt and Wife Foundation. The foundations had no influence on the study design, execution, analysis or interpretation of the data. Co-authors had nothing to disclose. Acknowledgement We wish to thank the staff at the ICUs in Stavanger University Hospital and Aarhus University Hospital. References
Strengths and limitations In our assessment of the possible impact of prolonged cooling on biomarker levels, the t48 and t72 samples were of specific interest, since treatment of patients was identical up to t24. The possible effects of prolonged TTM would, therefore, not be seen before t48. We saw a tendency towards differing biomarker levels between TTM24 and TTM48 in our NSE admission samples, suggesting a skewness with regards to the severity of the initial ischemic insult. Furthermore, we found a near-significant difference between the two TTM-groups in terms of the biomarker change from admission to t24, which was possibly a consequence of the differences found in the admission sample. These are probably random findings, since no differences were found in the baseline characteristics (Table 1) and the same skewness was not present in our S-100b admission samples. All samples were gathered and analysed at one particular laboratory in Denmark, in order to minimise the variation between the analytical methods, which are reported to vary by up to 36% between laboratories [18]. The samples were analysed in two batches, to take the time-limit recommendations for storing the samples into account. The biomarker results were blinded from the treating physicians, minimising the risk of a “self-fulfilling prophecy”. Furthermore, a guide to standardised prognostication and withdrawal of care was used in the two participating centres, improving the validity of our results. The primary weaknesses of our study were the small sample size and the missed inclusions. The difference in the number of percutaneous coronary interventions, performed between the missed inclusions and included patients (Table 1) could be due to early deaths in the missed inclusion group, albeit no difference in the days to death between the missing and included patients was found. The reason for the difference in the performed pci was probably a random finding due to our small sample size.
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