Simplifying the use of prognostic information in traumatic brain injury. Part 2: Graphical presentation of probabilities
Notice bibliographique
Résumé
OBJECTIVE Clinical features such as those included in the Glasgow Coma Scale (GCS) score, pupil reactivity, and patient age, as well as CT findings, have clear established relationships with patient outcomes due to neurotrauma. Nevertheless, predictions made from combining these features in probabilistic models have not found a role in clinical practice. In this study, the authors aimed to develop a method of displaying probabilities graphically that would be simple and easy to use, thus improving the usefulness of prognostic information in neurotrauma. This work builds on a companion paper describing the GCS-Pupils score (GCS-P) as a tool for assessing the clinical severity of neurotrauma. METHODS Information about early GCS score, pupil response, patient age, CT findings, late outcome according to the Glasgow Outcome Scale, and mortality were obtained at the individual adult patient level from the CRASH (Corticosteroid Randomisation After Significant Head Injury; n = 9045) and IMPACT (International Mission for Prognosis and Clinical Trials in TBI; n = 6855) databases. These data were combined into a pooled data set for the main analysis. Logistic regression was first used to model the combined association between the GCS-P and patient age and outcome, following which CT findings were added to the models. The proportion of variability in outcomes “explained” by each model was assessed using Nagelkerke’s R 2 . RESULTS The authors observed that patient age and GCS-P have an additive effect on outcome. The probability of mortality 6 months after neurotrauma is greater with increasing age, and for all age groups the probability of death is greater with decreasing GCS-P. Conversely, the probability of favorable recovery becomes lower with increasing age and lessens with decreasing GCS-P. The effect of combining the GCS-P with patient age was substantially more informative than the GCS-P, age, GCS score, or pupil reactivity alone. Two-dimensional charts were produced displaying outcome probabilities, as percentages, for 5-year increments in age between 15 and 85 years, and for GCS-Ps ranging from 1 to 15; it is readily seen that the movement toward combinations at the top right of the charts reflects a decreasing likelihood of mortality and an increasing likelihood of favorable outcome. Analysis of CT findings showed that differences in outcome are very similar between patients with or without a hematoma, absent cisterns, or subarachnoid hemorrhage. Taken in combination, there is a gradation in risk that aligns with increasing numbers of any of these abnormalities. This information provides added value over age and GCS-P alone, supporting a simple extension of the earlier prognostic charts by stratifying the original charts in the following 3 CT groupings: none, only 1, and 2 or more CT abnormalities. CONCLUSIONS The important prognostic features in neurotrauma can be brought together to display graphically their combined effects on risks of death or on prospects for independent recovery. This approach can support decision making and improve communication of risk among health care professionals, patients, and their relatives. These charts will not replace clinical judgment, but they will reduce the risk of influences from biases.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».