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1312 C.Sandroni et al./ Resuscitation 84 (2013) 13101323

Clinical examination: included every clinical sign that can be

collected during a bedside neurological examination. For exam-

ple, brainstem reflexes, GCS and its components, and myoclonus.

Clinical signs that require instrumental recording for collection

(e.g. seizures) were not included in this category. Electrophysiology: those indices require the recording of bio-

electrical signal from the central nervous system. They include

electroencephalogram(EEG) andevoked potentials (EPs). Wealso

considered forinclusion studies in which theEEG signalhad been

electronically analysed to produce a summary variable, such as

amplitude-integrated EEG (aEEG) or bispectral index (BIS). Biomarkers: we limited our review to the two most commonly

available serum biomarkers, neuron specific enolase (NSE) and

S-100B protein. Imaging: neuroimaging predictors that were assessed in our

reviewincludedcomputed tomography (CT),magneticresonance

imaging (MRI) and single-photon emission computed tomogra-

phy (SPECT).

Since we were interested only in the prediction of outcome

in comatose patients in the acute phase after resuscitation, we

included only studies where the outcome predictor was evaluated

within 7 days from cardiac arrest.

2.1.3. Outcome

We included only studies in which the neurological outcome

was described using the five Cerebral Performance Categories

(CPC)10 (See Table E1 on Electronic Supplementary Material [ESM])

or in such a manner that an equivalent CPC could be determined.

In those studies, the outcome is usually dichotomized as poor or

good according to a predefined CPC threshold, either CPC 45 vs.

13 or CPC 35 vs. 12. We accepted both of those definitions for

ourreview. When no thresholdhad been defined, we dichotomized

outcomes as CPC 45 vs. 13.

Supplementary material related to this article can be found,

in the online version, at http://dx.doi.org/10.1016/j.resuscitation.

2013.05.013.

In order to calculate both the outcome variables and their con-

fidence intervals, we included only studies where the complete

contingency table (i.e.,the numberof true/false negatives andposi-

tives for prediction of poor outcome) was reported, or could be

calculated from reported data.

2.1.4. Study type

Only clinical prognostic accuracy studies published in English,

French, German, Italian or Spanish as full-text articles on indexed

journals were included. Reviews, case reports and studies pub-

lished in abstract form were excluded. No publication date or

publication status restrictions were imposed.

2.2. Search strategy

We searched MEDLINE via PubMed, Scopus and the Cochrane

Database of Systematic Reviews using the search strings included

into the ESM Table E2.



2013.05.013.

The automatic alert system of PubMed was activated to identify

further studies published during the process of data extraction and

analysis. The reference lists of relevant studies were scanned in

order to identify other studies of interest.Last search was launched

on February 6, 2013.

For each of the four types of outcome predictors, two authors

performed a blinded and independent eligibility assessment. Dis-

agreements between reviewers were resolved by consensus.

2.3. Statistical methods

Foreachstudyincluded in thefinalanalysis, wecalculated sensi-

tivity, specificity, falsepositiverate (FPR)expressedas 1-specificity,

positive predictive value (PPV), expressed as TP/(TP+ FP) and posi-

tive likelihood ratio (LR+). For case series, where only the number

of true and false positives is known, we calculated only PPV.

In cases when a 100% sensitivity or specificity was encountered,

the value 0.5 was added to each cell of the abcd contingency table

in order to avoid division by zero in LR calculation.

Pooling of the indices was made for studies having in common

similar predictors, timepoints and outcome definitions. Confidence

intervals for pooled values of proportions were calculated using

the F distribution method, according to Blyth.11 If the value of

the proportion was 0% or 100%, a z-critical value for one-sided

confidence interval was used instead of the two-sided value, as

recommended.12,13 Pooled values of LR+ with relevant confidence

intervals were calculated according to the DerSimonianLaird

random effect model. Heterogeneity of pooled studies for sensi-

tivity/specificity and LR+ was estimated by: (1)G2 and Qstatistics

respectively; (2) I2 (inconsistency). Heterogeneity was regarded as

significant whenp50%.

2.4. Evidence appraisal

Given the absence of specific GRADE recommendations on

prognostic accuracy studies, we adapted the GRADE recommen-

dations for diagnostic accuracy studies7 to rate the quality of

evidence. Evidence evaluation was performed independently by

two authors.

According to the GRADE methodology7 the quality of evidence

started as high and was graded down based on the following fac-

tors: (1) limitations; (2) indirectness; (3) inconsistency; and (4)

imprecision. Publication bias was not considered, given the diffi-culty of measuring it in prognostic studies.14

In order to evaluate the presence of limitations (risk of bias),

the following information was extracted from included studies:

inclusion of a consecutive cohort of patients; blinding of both

treatmentteam and outcome or indexevaluators; exclusion of non-

neurological causes of death; exclusion of previous neurological

diseases; exclusionof sedation (for indexes based on clinical exam-

ination or EEG); exclusionof paralysis (for indexes based on clinical

examination); length of follow-up.

Given the importance of the risk of self-fulfilling prophecy, lim-

itations were graded as serious when the treating team was not

blinded to the results of the predictor of poor outcome that was

being studied, regardless of the presence of other limitations.

According to the GRADE methodology, the rating should bemodified upwards when the magnitude of effect is large. For the

purpose of our study, we considered a high predictor performance,

definedas a LR+>10,to be equivalent to a large magnitudeof effect.

Indirectnesswasdeemed present when thecharacteristics of the

study population did not completely correspond to that described

in the inclusion criteria, for example when a study included a

minority of patients treated using TH whose data could not be

separately analysed.

Inconsistency was evaluated after pooling. Inconsistency was

graded as serious when heterogeneity was significant (p< 0 .1 or

I2 >50%) for either sensitivity or specificity, and it was graded as

very serious when heterogeneity was significant for both of them.

Imprecision. When evaluating the accuracy of predictors of

poor outcome in critically ill patients, avoiding false positives is
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C. Sandroni et al. / Resuscitation 84 (2013) 13101323 1313

particularly important in order to avoid falsely pessimistic pre-

dictions. Ideally, for the prediction of a poor outcome the rate of

false positives should be zero. However, even a zero FPR has little

value when the precision of its estimate is low, i.e., its confidence

interval (CI) is large. We considered the FPR and the precision of

its estimate to be the most important parameters of the indices

included in our review. Imprecision was graded as serious when

the upper 95% CI of the FPR estimate was greater than 5%, and

it was graded as very serious when this value was more than

10%.

3. Results

3.1. Study selection (Fig. 1)

The initial search produced 935 records from PubMed, 392

records from Scopus and 11 records from the Cochrane Database

of Systematic Reviews. Thirty-four additional records were identi-

fied through forward search. After duplicate removal and abstract

screening, 213 studies were considered for full-text analysis.

Among them, 163 were excluded because they did not fulfil inclu-

sion criteria.The remaining 50 studies were included in ourreview.

Excluded studies with reasons for their exclusion are listed in theESM Table E3 (see Fig. 1).



2013.05.013.

3.2. Study characteristics

The characteristics of the 50 included studies (2828

patients) are summarised in Table 1. In 38/50 studies (76%)

poor outcome was defined as vegetative state or death(CPC 45), while in the remaining 12/50 studies (24%) poor

outcome was defined as severe disability, vegetative state

or death (CPC 35). Eight studies were based on clinical

examination,1522 eighteen on electrophysiology,2340 eight

on biomarkers,4148 nine on neuroimaging,4957 and seven on

multiple predictors.5864

Sensitivity, FPR (1-specificity), and the quality of evidence for

indices based on clinical examination, electrophysiology, biomark-

ers and neuroimaging are reported on Tables 2a2d. The evidence

profiles of predictors are reported on ESM Tables E4ad. Results

of individual studies are reported in detail on ESM Tables

E5ad.


in the online version, at http://dx.doi.org/10.1016/j.resuscitation.2013.05.013.

PubMed: 935 records

Scopus: 392 records

Cochrane Database of systematicreviews: 11 records

1338 records34 additional records identified

through forward search

1372 records screened

1159 discarded

(duplicates or excluded aftertitle and abstract evaluation)

213 full-text articlesassessed for eligibility

163 full-text excluded due to

83 Patient characteristics

22 Intervention characteristics

7 Comparison characteristics26 Outcome characteristics

20 Study characteristics

2 Data could not be extracted3 Unavailablestudies

50 studies included inqualitative and quantitative

synthesis

(meta-analysis)

Identification

Screening

Eligibility

Included

Fig. 1. Flow-chart of study selection.
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Table 1

Characteristics of the included studies.

Author, year,

Reference

IHCA or

OHCA

No. of

patients

Males, % VF/VT % Mean age, ys [SD]

or median (range)

Predictor(s) Definition of

poor outcome

(CPC)

Timing of outcome

assessment

Clinical Examination

Bertini 198915 OHCA 34 85 74 66 [10.4] PLR, MR 45 vs. 13 ICU discharge

Earnest 197916 OHCA 117 74 N/A 62 (median) PLR, OCR, MR 35 vs. 12 Hospital discharge

Fischer 200617 OHCA 62 76 N/A 55 [16] GCS 45 vs. 13 12 mo

Krumholz 198818

Mixed 114 61.4 N/A 57 [ 17.9] Myoclonus 45 vs. 13 6 moPfeifer 200519 Mixed 97 71 47 63 (1790) GCS 45 vs. 13 1 mo

Thomke 200520 Mixed 50 52 88 54 (2083) Myoclonus 45 vs. 13 48 mo

Wijdicks 199421 OHCA 107 62 38 63 (2786) Myoclonus 45 vs. 13 6 mo

Young 199022 N/A 11 73 N/A 57 [16.7] Myoclonus 45 vs. 13(a) Hospital discharge

Electrophysiologic studies

Bauer 200323 Mixed 305 68 57 57 (1689) SSEPs 45 vs. 13 12 mo

Berkhoff200024 N/A 9 89 N/A 58 (2483) EEG (Alpha coma) 45 vs. 13 12 mo

Brunko 198725 OHCA 50 N/A N/A 62 [17] SSEPs 45 vs. 13 Hospital discharge

Chockroverty 197526 N/A 12 83 N/A 55 [15.9] EEG 45 vs. 13 Hospital discharge

Gendo 200127 N/A 25 80 60 59 (4287) SSEPs 35 vs. 12 6 mo

Grindal 197728 N/A 14 86 N/A 58 [16.3] Alpha coma 45 vs. 13 (a) 2 mo

Kaplan 199929 N/A 18 72.2 N/A 60 [16.2] EEG 45 vs. 13 10 mo

Madl 200130 Mixed 162 65 49 57 [16] SSEPs 35 vs. 12 6 mo

Nakabayashi 200131 OHCA 30 67 N/A 63 (1690) SSEPs 45 vs. 13 9 mo

Rothstein 199132 OHCA 40 58 N/A 72 (1991) EEG 45 vs. 13 2 mo

Rothstein 200033 OHCA 50 56 N/A 71 (1991) SSEPs 45 vs. 13 1 mo

Scollo-Lavizzari 198734 N/A 26 65 N/A 61 (1677) EEG 35 vs. 12 N/AStelzl199535 N/A 13 62 N/A 67 (4880) SSEPs 45 vs. 13 N/A

Tiainen 200536 OHCA 30 73 100 58 (1875) SSEPs 45 vs. 13 6 mo

Vignaendra 197437 OHCA 8 88 N/A 53 [13] EEG 45 vs. 13 (a) 14 d

Zanatta 201238 N/A 6 N/A 100 63 (3589) SSEPs 45 vs. 13 3 mo

Zandbergen 2006a39 N/A 407 67 68 63 [14] SSEPs 45 vs. 13 12 mo

Zhang 201140 N/A 77 46 0 57 [19.2] EEG, SSEPs, BAEPs 45 vs. 13 6 mo

Biomarkers

Hachimi-Idrissi 200241 OHCA 58 N/A N/A 64 [ 3] S-100 45 vs. 13 Hospital discharge

Mussack 200242 OHCA 20 70 50 71 S-100B 35 vs 12 12 mo

Reisinger 200743 Mixed 177 63 53 65 [15] NSE 45 vs. 13 6 mo

Rosen 199844 OHCA 41 76 80 68 (2189) S-100 45 vs. 13 Hospital discharge

Rosen 200145 OHCA 66 76 79 68[14.6] NSE, S-100 35 vs 12 12 mo

Samaniego 201146 Mixed 32 53 38 55 (1986) NSE 45 vs. 13 3 mo

Steffen 201047 Mixed 73 75 55 64 NSE 35 vs 12 ICU discharge

Tiainen 200348 OHCA 34 71 100 59 (1875) NSE, S-100B 35 vs 12 6 mo

NeuroimagingChoi 200849 OHCA 28 75 28.5 54 (2786) Brain CT 45 vs. 13 Hospital discharge

Choi 201050 OHCA 39 72 15 49 (1889) Brain MRI 35 vs 12 3 mo

Della Corte 199351 N/A 11 45.5 N/A 40 [16.6] Brain SPECT 45 vs. 13 6 mo

Els 200452 N/A 12 N/A N/A 53 (2771) Brain MRI 45 vs. 13 6 mo

Mlynash 201053 Mixed 12 N/A N/A 52 [17] Brain MRI 45 vs. 13 6 mo

Morimoto 199354 OHCA 53 66 26.4 51 [22.9] Brain CT 45 vs. 13 7 d

Torbey 200455 N/A 32 56 40.6 64 [16.5] Brain CT 45 vs. 13 Hospital discharge

Wijdicks 200156 Mixed 10 50 N/A 57 [14.1] Brain MRI 35 vs. 12 N/A

Wijman 200957 Mixed 10 N/A N/A 54 [15] Brain MRI 45 vs. 13 6 mo

Multimodal prognostication

Bassetti 199658 N/A 60 82 N/A 62 (1986) BR, GCS, MR, EEG,

SSEPs

45 vs. 13 12 mo

Berek 199559 OHCA 30 N/A 70 61 (1886) Brain MRI, SSEPs 35 vs. 12 1 mo

Edgren 198760 N/A 32 47 N/A 71 [8.5] BR, MR,EEG 35 vs. 12 6 mo

Topcuoglu 200961 Mixed 22 59 N/A 56 [16.9] GCS, FOUR score,

brain MRI

45 vs. 13 3 mo

Young 200562 Mixed 75 61 65 66 [13] PLR, CR, VOR, MR,myoclonus, SSEPs,

EEG

45 vs. 13 3 mo

Zandbergen 2006b63 N/A 407 67 68 63 [14] BR, MR, myoclonus,

NSE, S-100B, SSEPs,

EEG

45 vs. 13 6mo

Zingler 200364 Mixed 27 48 N/A 61 [17.3] NSE, S-100B, SSEPs 45 vs. 13 3 mo

Abbreviations: BAEPs = B rain stem Auditory Evoked Potentials; CPC = C erebral Performance Category; CR = C orneal Reflex; CT = C omputed Tomography;

EEG =Electroencephalogram; GCS= Glasgow Coma Score; IHCA=In Hospital Cardiac Arrest; MR=Motor Response; MRI= Magnetic Resonance Imaging; N/A= Not

Available; NSE= Neuron-Specific Enolase; OCR= OculoCephalicReflex; OHCA = Out of Hospital Cardiac Arrest; PLR= Pupillary Light Response; SSEPs = Somatosensory Evoked

Potentials; SPECT = Single-Photon Emission Computed Tomography; FOUR score= Full Outline of UnResponsiveness score; VOR= Vestibulo-Ocular Reflex.a Defined by the reviewer.


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Table 2a

Summary of findings for predictors based on clinical examination.

Timing Index Reference Sensitivity % [95% CI] FPR % [95% CI] No. of patients Quality of evidence

CPC 45 vs. 13

On admission GCS4 Fisher, 198817 74 [5886] 40 [19 64] 62 Very low

Motor score = 13 Bertini, 198915 89 [6599] 81 [5496] 34 Very low

Myoclonus status Wijdicks, 199421 46 [3557] 0 [014] 107 Low

At 612 h PLR absent Bertini, 198915 33 [1262] 25 [752] 31 Very low

>1 BR absenta Bassetti, 199658 21 [1035] 0 [0 22] 60 Very low

Motor score = 13 Bertini, 198915 91 [7998] 62 [4180] 72 Very lowBassetti, 199658

At24h OVR absent Young, 200562 42 [2659] 0 [031] 44 Very low

PLRabsent Bertini, 198915 21 [1725] 9 [418] 496

Very lowYoung, 200562

Zandbergen, 200663

CR absent Young, 200562 38 [3343] 18 [1030] 465Very low

Zandbergen, 200663

PLR and CR absent Zandbergen, 200663 14 [1018] 5 [117] 386 Very low

Motor score =1 Young, 200562 63 [4876] 6 [030] 67 Low

Motor score = 12 Zandbergen, 200663 78 [7382] 45 [2962] 395 Very low

Motor score= 13 Bertini, 198915 84 [7293] 46 [2767] 83Very low

Bassetti, 199658

Myoclonus (status) Young, 200562 9 [713] 0 [03] 471Moderate

Zandbergen, 200663

At 48 h PLR absent Bertini, 198915 19 [1524] 4 [115] 375Very low

Zandbergen, 200663


Motor score =12 Zandbergen, 200663 75 [7080] 41 [2461] 351 Very low

Motor score= 13 Bertini, 198915 92 [8098] 14 [433] 77Very low

Bassetti, 199658

CR absent Zandbergen, 200663 31 [2636] 10 [227] 341 Very low

At 3648 h Myoclonus status Krumholz, 198818 8 [511] 0 [05] 464Low

Zandbergen, 200663

At 72 h PLR absent Bertini, 198915 18 [1523] 0 [08] 382Low

Zandbergen, 200663


FOURscore


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Table 2b

GRADE summary of findings for predictors based on electrophysiology.

Timing Index Reference Sensitivity % [95% CI] FPR% [95% CI] No. of patients Quality of evidence

CPC 45 vs. 13

At 8 h SSEPs N20 absent Brunko, 19872584 [7293] 0 [012]

80 Low

Nakabayashi,

200131

At 24 h SSEPs N20 absent Stelzl, 199535

46 [4053] 0 [05]

295 Moderate

Tiainen, 200536

Zandbergen,

200639

SS EPs N7 0 a bs ent Zan dber gen ,

20063930 [2337] 20 [1035] 212 Very low

At 48 h SSEPs N20 absent Rothstein, 200032

46 [4052] 0 [05]

328 Moderate

Zanatta, 201238

Zandbergen,

200639

Zingler, 200364

SSEPs N70 absent Zandbergen,

20063926 [1835] 17 [636] 148 Very low

At 48 h EEG malignant grade

(Synek)

Rothstein, 199133 42 [2363] 0 [019] 40 Very low

At 72 h SSEPs N20 absent Stelzl, 19953546 [4052] 0 [09]

293 Low

Zandbergen,

200639

SSEPs N20mono or

bilaterally absent

Berek, 199559 86 [42100] 0 [026] 17 Very low

EEG statu s e pile pticus Zan dber gen ,

2006399 [613] 8 [127] 283 Very low

At 72 h SSEPs N 20 a bsent Bauer, 200323

45 [3951] 1 [05]

408 Low

Bassetti, 199658

Young, 200562

SSEPs N20 absent Berkhoff, 200024 PPV 100 [48100] 5 Very low

SSEPs N70 absent Bauer, 200323

49 [4454] 8 [416]

470 Very low

Zandbergen,

200639

Young, 200562

EEG Grade IVV Bassetti, 199658 42 [2857] 0 [024] 59 Very low

EEG Burst-suppression Zandbergen,

200639 15 [1119] 2 [012]

349 Very low

Young, 200562

EEG voltage2021V Zandbergen,200639

28 [2334] 0 [06] 355 Low

Young, 200562

At 17d SSEPs N20 absent Zhang, 201140 70 [5780] 0 [024] 77 Low

Unfavourable EEG Zhang, 201140 97 [89100] 64 [3189] 77 Very low

Unreactive EEG Zhang, 201140 92 [8397] 45 [1777] 77 Very low

BAEP wave V absent Zhang, 201140 62 [4974] 9 [041] 77 Very low

At 13d EEG a lpha ( theta) c oma Berkhoff, 200024 PPV 100 [84100] 17 Very low

Vignaendra, 197437

At 16d EEG alpha coma Chokroverty,

197526PPV 88 [7596] 43 Very low

Grindal, 197728

Kaplan, 199929

CPC 35 vs. 12

At 24 h SSEPs N20 absent Madl, 200030 37 [2946] 0 [08] 159 Low

SSEPs N70>127ms or

absent

Gendo, 20012788 [8192]

2 [012] 187 Very low

Madl, 200030

EEG Grade IIIV Edgren, 198760 36 [1365] 0 [022] 26 Very low

At 48 h EEG Grade IIIV Edgren, 198760 36 [1169] 0 [024] 22 Very low

At 72 h EEG Grade IVV Scollo-Lavizzari,

19873450 [2971] 0 [078] 26 Very Low

At 24 h EEG alpha coma Edgren, 198760 PPV 100 [37100] 3 Very low

At 48 h EEG alpha coma Edgren, 198760 PPV 83 [36100] 6 Very low

Abbreviations:BAEP= Brainstem Auditory Evoked Potentials; CI= ConfidenceIntervals; CPC= Cerebral Performance Categories; EEG= Electroencephalogram;FPR = False Pos-

itive Rate; No= Number; SSEPs = Somatosensory Evoked Potentials.


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Table 2c

GRADE summary of findings for predictors based on biomarkers.

Timing Index Reference Cutoff (g l1) Sensitivity % [95% CI] FPR% [95% CI] No. of patients Quality of evidence

CPC 45 vs. 13

On admission S- 10 0B Ha chimi-I drissi , 2 00 241 0.7 67 [4882] 13 [334] 56 Very low

At 24 h NSE Zandbergen, 200663 33 48 [4255] 0 [08] 272 Moderate

NSE Zingler, 200364 47.6 53 [2877] 0 [026] 27 Very low

S-100B Rosen, 1 99844 0.2 77 [4695] 19 [542] 34 Very low

S- 10 0B Ha chimi-I drissi , 2 00 241

0.7 57 [5163] 10 [421]

330 Very low

Zandbergen, 200663

S-100B Zingler, 2 00364 5.2 35 [1462] 0 [026] 27 Very low

At 48 h NSE Zandbergen, 200663 33 61 [5468] 0 [08] 241 Low

NSE Reisinger, 200743 65 62 [4775] 0 [03] 156 Moderate

S-100B Rosen, 1 99844 0.2 79 [4995] 0 [012] 38 Very low

S-100B Zandbergen, 200663 0.7 51 [4458] 5 [118] 238 Very low

At 72 h NSE Samaniego, 20114633 55 [4863] 3 [014]

221 Very low

Zandbergen, 200663

NSE Reisinger, 200743 80 43 [2958] 0 [03] 152 Moderate

S-100B Zandbergen, 200663 0.7 42 [3450] 0 [08] 207 Low

CPC35 vs. 12

At 12-24h S-100B Tiainen, 200348 0.19 59 [3382] 0 [017] 33 Very low

S-100B Mussack, 2 00242 0.76 53 [2877] 0 [063] 20 Very low

At 24 h NSE Tiainen, 200348 13.3 59 [3382] 0 [017] 33 Very low

At 48 h NSE Tiainen, 200348 8.8 75 [4893] 0 [017] 32 Very low

NSE Rosen, 200145 25.0 37 [2254] 0 [012] 61 Very low

S-100B Tiainen, 200348 0.12 88 [6298] 0 [017] 32 Very low

S-100B Rosen, 2 00145 0.25 68 [5182] 0 [012] 61 Very low

At 72 h NSE Rosen, 200145 15.0 71 [5584] 0 [012] 65 Very low

NSE Steffen, 201047 22.4 86 [7892] 10 [227] 133 Very low

Abbreviations:CI= Confidence Interval; CPC= Cerebral Performance Categories; FPR= False Positive Rate; No= number; NSE= Neuron-Specific Enolase.

Presence ofmyoclonus or myoclonus status predicted death or

vegetative state with 0% [014] FPR when recorded on admission,

and remained predictive during the first 72h, with high precision

(95%CI 03 at 24h) but low sensitivity (89%; see Table 2a).

No value of eitherGCSor GCSmotor score consistently predicted

CPC 45 with zero FPR.

3.4. Electrophysiology

Bilateral absence of the N20 wave of short-latency somatosen-

sory evoked potentials (SSEPs) predicted death or vegetative state

with 0% [012] FPR as early as 8 h from cardiac arrest, and it

remained predictive during the first 72h with a consistent sen-

sitivity (4546%). A single large study on 159 patients30 confirmed

bilateral absence of SSEP N20 at 24h to be an accurate predictor of

CPC 35 as well (FPR 0% [08]). Among all patients in whom N20

SSEP wave was absent in the first 7 days from cardiac arrest there

was only one case of false positive result.62

Conversely, none of the studies assessing the predictive value

of a delayed or absent N70 SSEP wave documented a 0% FPR (seeTable 2b).

AGradeIIIVEEGaccordingto Edgrenet al60 at 24predicted poor

outcome (CPC 35) with 0% [022] FPR.EEGGrades IVVaccording

to Synek et al65 and Bassetti et al58 at 48 h and 72h respec-

tively, predictedpooroutcome (CPC 45) with 0%FPR (95% CIs019

and 024 respectively) and 42% sensitivity (see ESM Table E8 for a

comparison of EEG grading systems).



2013.05.013.

In two large cohort studies,62,63 a low-voltage EEG (2021V)

at 24h72 h predicted poor outcome with 0% [08] FPR.

Presence ofalpha coma was not consistently associated with

poor outcome.24,37,60

3.5. Biomarkers

The highest threshold of NSE or S-100B serum concentrations

associated with a 0% FPR varied with studies, timing and definition

of poor outcome.

For poor outcome defined as CPC 45, this threshold for NSE

was 47.6g l1, 65g l1 and 80g l1 at 24 h, 48 h, and 72 h,respectively (see Table 2c).43,64 For S-100B, single studies reported

a threshold of 5.2g l1 at 24 h64 andof 0.7g l1 at72h.63

For poor outcome defined as CPC 35, this threshold for NSE

was 13.3g l1 at24hand25g l1 at48 h while for S-100B itwas

0.76 and0.25g l1, respectively. At 72h, a single study45 reported

an NSE threshold of 15g l1 for 0% FPR, but in a larger study47 a

NSE level of 22.4g l1 was associated with a 10% [227] FPR. All

studies in which poor outcome was defined as CPC 35 had a very

low quality of evidence.

3.6. Imaging

The number of patients studied with imaging techniques wasrelatively small, except for CT scan.

In 3 studies on a total of 113 patients, diffuse brain swelling on

brain CT scanwithin 72h predicted an almost invariably poor out-

come (FPR 5% [025]) with 54% [4364] sensitivity (see Table 2d).

In two small studies (total 22 patients), presence of extensive

brain abnormalities at 432h52 or reduction of absolute diffusion

coefficient (ADC) below 650106 mm2/s in more than 10% of

brain volume at 49108h57 on diffusion weighted (DWI) MRIpre-

dicted poor outcome with 0% FPR but wide 95% CI (045 and 078,

respectively).

Elevated lactate on MRI spectroscopy within 96h predicted a

poor outcome (CPC 35) with 71% [4292] sensitivityand 0%[035]

FPR in a study including 21 patients.59 Reduction of either cere-

bral blood flow (CBF) below 30ml/100g/min or cerebral oxygen
http://dx.doi.org/10.1016/j.resuscitation.2013.05.013http://dx.doi.org/10.1016/j.resuscitation.2013.05.013http://dx.doi.org/10.1016/j.resuscitation.2013.05.013http://dx.doi.org/10.1016/j.resuscitation.2013.05.013


9/14


Table 2d

GRADE summary of findings forpredictors based on imaging.

Timing Index Reference Sensitivity % [95% CI] FPR% [95% CI] No. of patients Quality of evidence

CPC 45 vs. 13

At 432 h Extensive DWI alterations ( MRI) Els, 2 00452 100 [65100] 0 [045] 12 Very low

At 72 h Brain swelling (CT) Choi, 200849 54 [4364] 5 [025] 113 Very low

Morimoto, 199354

Torbey, 200455

Median 80h (IQR

55117)

Abnormalities in basal ganglia

(MR-DWI)

Mlynash, 201053 100 [55100] 43 [1082] 12 Very low

Diffuse moderate to severe cortical

FLAIR-DWI alterations (MRI)

Mlynash, 201053 80 [2899] 0 [035] 12 Very low

At 49108 h > 10% Brain volume with ADC 2021V at

2472 h, and absence ofPLR at72 h each predicted death orvegeta-

tive state with zero FPRand narrowCIs,and (b)absence of SSEP N20

wave at 24h predicted death, vegetative state or severe disability

with zero FPR and narrow CIs. In addition, a serum NSE65g l1

at48hor80g l1 at 72h also predicteddeathor vegetative state

with 0% FPR and low CIs in one study, but the NSE thresholds for

0% FPR prediction varied largely and inconsistently. The quality of

evidence of the vast majority of the studies included in our review

was low or very low and only a few studies reported blinding of

the treating team from the results of the investigated predictor.

These predictors need to be confirmed in a prospective validation

study.

6. Conflict of interest statement

Claudio Sandroni, Fabio Cavallaro, Clifton Callaway, Tommaso

Sanna,SoniaDArrigoand Michael Kuiperhave no conflicts of inter-

est to declare.

Jerry Nolan is Editor-in-Chief of Resuscitation.

Acknowledgements

We gratefully thank the following investigators for having pro-

vided original data from their studies:

1. Dr. Albert Hijdra, Department of Neurology, Academic Medical

Centre, University of Amsterdam, The Netherlands;

2. Dr. Michael Mlynash, Stanford Stroke Centre, Department of

Neurology and Neurological Sciences, Stanford University, Palo

Alto, CA, USA

3. Dr. KyuNam Park, Department of EmergencyMedicine, Seoul St.

Marys Hospital, Seoul Korea;

4. Dr. Johann Reisinger, Department of Internal Medicine/Cardiology, Krankenhaus Barmherzige Schwestern, Linz, Austria

5. Dr. Mehmet Akif Topcuoglu, NeuroICU, Hacettepe University

Hospitals, Ankara, Turkey

6. Dr. Eveline Zandbergen, Rijnstate Hospital, Arnhem, The

Netherlands.

We also gratefully thank Dr. Lorenzo Compieta for providing

statistical advice during data analysis.

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Pronostico Neurologico Paro Cardiaco

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