The Relative Impact of Clinical and Investigational Factors to Predict the Outcome in Stroke Patients
Notice bibliographique
Résumé
OBJECTIVE: As stroke is still considered a significant cause of mortality and morbidity, it is crucial to find the factors affecting the outcome in these patients. We aimed to interpret the various clinical and investigational parameters and establish their association with the outcome in stroke patients. MATERIALS AND METHODS: This is a retrospective, cross-sectional study, conducted in the Department of Neurology between June 2019 to November 2021. The study involved the review and analysis of medical records pertaining to 264 patients, admitted with the diagnosis of stroke. Various clinical, radiological, and electroencephalographic (EEG) patterns in stroke patients were analyzed and their association with outcome was established. The association between the studied variables was performed by the logistic regression (LR) and presented as odds ratio (OR) and 95% confidence interval (CI). RESULTS: The study sample consisted of 264 patients. Males comprised 165 (62.5%) with the mean participant age of 57.17 ± 18.7 3 years (range: 18-94). Patients younger than 50 years had a better likelihood of a good outcome in comparison to patients older than 50. The admission location was the most significant factor in predicting the outcome ( P = 0.00) in favor of inpatient department and outpatient department (OPD), in contrast to patients admitted directly to intensive care unit (ICU). Normal EEG was associated with good outcome ( P = 0.04; OR, 3.3; CI, 1.01-10.88) even after adjustment of the confounders, whereas patients having marked EEG slowing had a poor outcome ( P = 0.05; OR, 2.4; CI, 0.65-8.79). Among the clinical parameters, hemiparesis ( P = 0.03), trauma ( P = 0.01), generalized tonic-clonic seizures (GTC) ( P = 0.00), and National Institutes of Health Stroke Scale of more than 4 were more likely associated with a poor outcome as well as the presence of intracranial hemorrhage (ICH) or infarction in the cortical and cortical/subcortical locations were associated with poor outcomes. After adjustment of confounders, the factors found to have prognostic significance in favor of good outcomes were inpatients or OPD referrals and normal EEG while direct admission to ICU, marked slowing on EEG, and presence of ICH were found to be associated with poor outcome. CONCLUSION: Certain patterns are predictive of good or worse outcomes in stroke patients. Early identification of these factors can lead to early intervention, which in turn might help in a better outcome. The results of the study, therefore, have some prognostic significance.
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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 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| 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 ».