Blood biomarkers for the prediction of outcome after cardiac arrest: an international prospective observational study within the Targeted Hypothermia versus Normothermia after Out-of-Hospital Cardiac Arrest (TTM2) trial
Notice bibliographique
Résumé
BACKGROUND: Prognostication of recovery in patients who are unconscious following cardiac arrest can be guided by concentrations of brain injury biomarkers in the blood. The optimal biomarker and cutoff concentrations for the prediction of outcome remain unknown. In this study, we aimed to evaluate which biomarker of brain injury is most accurate for predicting functional outcome after cardiac arrest, and to evaluate cutoff levels for the prediction of good and poor outcome. METHODS: This study was a prospective, international, observational biomarker study within the international Targeted Hypothermia versus Normothermia after Out-of-Hospital Cardiac Arrest (TTM2) trial including adults aged 18 years or older with a presumed cardiac cause or unknown cause of arrest. Patients were recruited from 24 European hospitals. Serum samples were collected at 0, 24, 48, and 72 h after admission to intensive care units. Concentrations of neuron-specific enolase, S100, neurofilament light, and glial fibrillary acidic protein were analysed with Elecsys electrochemiluminescence immunoassays. The primary outcome was 6-month good (modified Rankin Scale 0-3) or poor (modified Rankin Scale 4-6) functional outcome. Prognostic accuracy was evaluated by the area under the receiver operating characteristic curve (AUROC). The biomarker with the highest AUROC at each timepoint was compared with that of the second highest marker using DeLong's test. As pre-specified, to account for multiple comparisons using Bonferroni correction, a p value of less than 0·0125 was considered statistically significant. FINDINGS: Between April, 2018, and January, 2020, 113 (12%) of 932 eligible patients were excluded due to death, missed sampling, or missing outcome data. 661 (81%) of 819 included patients were male and 158 (19%) were female, the mean age was 64 years (SD 13), and 418 (51%) had a poor outcome. In patients who were unconscious, neurofilament light predicted functional outcome with AUROCs at 0, 24, 48, and 72 h of 0·77 (95% CI 0·73-0·80), 0·92 (0·90-0·94), 0·93 (0·91-0·95), and 0·93 (0·91-0·95), respectively. Glial fibrillary acidic protein achieved an AUROC of 0·74 (95% CI 0·70-0·77) at 0 h, 0·87 (0·84-0·90) at 24 h, 0·87 (0·84-0·90) at 48 h, and 0·87 (0·84-0·91) at 72 h. Neuron-specific enolase predicted functional outcome with an AUROC of 0·61 (95% CI 0·56-0·65) at 0 h, 0·78 (0·75-0·82) at 24 h, 0·85 (0·81-0·88) at 48 h, and 0·86 (0·82-0·89) at 72 h. S100 achieved an AUROC of 0·74 (95% CI 0·71-0·78) at 0 h, 0·84 (0·81-0·87) at 24 h, 0·79 (0·75-0·82) at 48 h, and 0·78 (0·74-0·82) at 72 h. Neurofilament light had a statistically significantly higher AUROC than the second highest marker, glial fibrillary acidic protein, at 24, 48, and 72 h (p<0·0001), but not at 0 h (p=0·27). INTERPRETATION: Neurofilament light is a highly accurate predictor of long-term outcome after cardiac arrest and superior to other relevant biomarkers evaluated in this study. FUNDING: The Swedish Research Council (Vetenskapsrådet), the Swedish Heart-Lung Foundation, the Stig and Ragna Gorthon Foundation, the Knutsson Foundation, the Laerdal Foundation, the Hans-Gabriel and Alice Trolle-Wachtmeister Foundation for Medical Research, the Bundy Academy at Lund University, Regional Research Support in Skåne, the Swedish Government, and Roche Diagnostics International.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».