Key prognostic risk factors linked to poor functional outcomes in cerebral venous sinus thrombosis: a systematic review and meta-analysis
Notice bibliographique
Résumé
BACKGROUND: Cerebral venous sinus thrombosis is a rare stroke with several clinical manifestations. Several studies have identified prognostic risk factors associated with poor functional outcomes and established predictive models. This systematic review and meta-analysis assessed the overall effect size of all prognostic risk factors. METHODS: A systematic review was conducted to explore all prognostic risk factors in studies published from the initial to June 2024 among 5 Databases included PubMed / Medline, Scopus, EBSCOhost, Web of Science, and Cochran Library. The quality of the methodology was analyzed using the Newcastle-Ottawa Scale. Data analysis was performed using the Statistical Package for Social Sciences (SPSS) version 29. RESULTS: Sixty-four studies involving 18,958 participants with a mean age of 38.46 years and females 63.03% were included in the quantitative meta-analysis. Functional outcomes were primarily measured using the Modified Rankin Scale (mRS), with scores ≥ 2 or ≥ 3 indicating poor outcomes in 35.00% and 60.00% of studies, respectively. For general information, age (InOR = 0.98, 95% CI 0.53-1.43), intracranial hemorrhage (OR = 3.79, 95% CI 2.77-5.20), and ischemic infarction (OR = 3.18, 95% CI 2.40-4.23) were associated with poor functional outcomes. For general and neurological symptoms, headache (OR = 0.22, 95% CI 0.17-0.29), seizure (OR = 2.74, 95% CI 1.76-4.27), focal deficit (OR = 4.72, 95% CI 3.86-5.78), coma (OR = 11.60, 95% CI 6.12-21.98), and consciousness alteration (OR = 7.07, 95% CI 4.15-12.04) were outstanding factors. The blood biomarkers of NLR (log OR = 1.72, 95% CI 0.96-2.47), lymphocytes (Cohen's d = -0.63, 95 CI -0.78--0.47), and D-dimer (lnOR = 1.34, 95% CI 0.87-1.80) were the three most frequently reported factors. Parenchymal lesion (OR = 4.71, 95% CI 1.12-19.84) and deep cerebral venous thrombosis (OR = 6.30, 95% CI 2.92-13.63) in radiological images were two frequently reported factors. CVST patients with cancer (OR = 3.87, 95% CI 2.95-5.07) or high blood glucose levels (OR = 3.52, 95% CI 1.61-7.68) were associated with poor functional outcomes. In the meta-regression analysis, ischemic infarction (P = 0.032), consciousness alteration (P < 0.001), and NLR (P = 0.015) were associated with mRS prediction. CONCLUSIONS: Pooled effect sizes revealed that ischemic infarction, headache, neurological focal deficit, lymphopenia, and cancer were significantly associated with poor functional outcomes, with low to moderate heterogeneity. Consciousness alterations/deterioration and deep cerebral venous thrombosis were also significant prognostic factors, albeit with substantial heterogeneity. The meta-regression analysis showed that the effect sizes of consciousness alterations/deterioration and NLR increased with worsening mRS scores. Other notable risk factors included age, intracranial hemorrhage, seizures, coma, D-dimer, parenchymal lesions, and hyperglycemia. This systematic review provides a comprehensive overview of the prognostic risk factors for poor functional outcomes in patients undergoing CVST, which can guide clinical decision-making and future research. TRIAL REGISTRATION: This systematic review and meta-analysis has been registered with INPLASY (International Platform of Registered Systematic Review and Meta-analysis Protocols), and the registration number is INPLASY202480072. The registration period is 14 August 2024.
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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 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,023 | 0,004 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».