Mortality in Cerebral Venous Thrombosis: Results from the National Inpatient Sample Database
Notice bibliographique
Résumé
BACKGROUND: Outcomes of cerebral venous thrombosis (CVT) vary from full recovery to death. Few studies have been performed examining epidemiologic and medical risk factors associated with high mortality in CVT. In this study, we examined the National Inpatient Sample (NIS) to determine the epidemiologic and medical risk factors associated with increased mortality from CVT. MATERIALS AND METHODS: Using the NIS from 2001 to 2008, patients who suffered from CVT were identified using the ICD-9 codes 437.6 (nonpyogenic thrombosis of intracranial venous sinus), 325 (phlebitis and thrombophlebitis of intracranial venous sinuses) and 671.5 (peripartum phlebitis and thrombosis, cerebral venous thrombosis, thrombosis of intracranial venous sinus). We analyzed the associations of demographic factors, risk factors, comorbidities, complications of CVT, and therapeutic interventions with in-hospital mortality. We performed a multivariate logistic regression analysis to determine which variables were independently associated with in-hospital mortality. RESULTS: 11,400 patients were hospitalized with CVT between 2001 and 2008. Two-hundred and thirty-two (2.0%) suffered in-hospital mortality. Patients 15-49 years old had the lowest mortality rate (1.5%) compared with 2.8% for patients aged 50-64 (p < 0.001) and 6.1% for patients ≥65 years old (p < 0.001). The most common condition associated with CVT was pregnancy/puerperium (24.6%), and these women had a low mortality rate (0.4%). On multivariate analysis, the comorbidity most strongly associated with increased risk of mortality was sepsis (mortality rate 15.6%, OR = 7.5, 95% CI = 4.79-11.53, p < 0.001). Malignancy, underlying autoimmune disease and substance abuse were also independently associated with mortality, but with lower mortality rates (<5%). Complications associated with increased risk of mortality included paralysis (8.0%, OR = 3.4, 95% CI = 3.17-6.96, p < 0.001), intracranial hemorrhage (8.7%, OR = 5.4, 95% CI = 4.38-7.96, p < 0.001), and hydrocephalus (15.0%, OR = 3.2, 95% CI = 5.54-15.11, p = 0.004). Demographic variables associated with decreased mortality on multivariate analysis were male gender (2.1%, OR = 0.62, 95% CI = 0.43-0.87, p = 0.006) and Asian/Pacific Islander race (OR = 0.00, 95% CI = 0-0.27, p < 001). CONCLUSIONS: CVT is associated with a low in-hospital mortality rate. Amongst patients suffering CVT, male gender and Asian/Pacific Islander race were independently associated with lower odds of in-hospital mortality when compared to their female and white counterparts, respectively. Septic patients with CVT have the greatest risk of in-hospital mortality. Hydrocephalus, intracranial hemorrhage, and motor deficits are also associated with higher risk of death. Our results build on previous evidence that serves to define a group of patients with CVT at high risk of early death.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 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 ».