Time Course of Venous Thromboembolism Events and Influence of Risk Factors in High Risk Medical Patients,
Notice bibliographique
Résumé
Abstract Abstract 4182 Background: Venous thromboembolism (VTE) prophylaxis has been identified in clinical guidelines as an appropriate strategy for high-risk medical inpatients as it results in reduced VTE events and reduced mortality. However, real life data regarding the timing of VTE events and the relationship between risk factors and VTE in this population is lacking. Further knowledge of the time course of recurrence and influence of risk factors in actual practice may help clinicians determine strategies regarding the frequency of clinical surveillance and the appropriate duration of treatment. Objective: To document the time course of symptomatic VTE events in high-risk medical patients in every day clinical practice and to relate the frequency of risk factors to the likelihood of VTE development. Methods: Charts from 1134 consecutive high-risk medical patients who were hospitalized in the Calgary region and discharged between January and February 2008 were abstracted using standardized case record forms. All hospitals in the region use a common unique patient identifier number, thus enabling the tracking of subsequent patient visits to the emergency room, inpatient admissions or outpatient visits occurring anywhere in the region's acute care system. Any identified patient was followed for a subsequent visit related to VTE. High-risk medical patients were defined as age > 60 years and having at least one of the following risk factors: malignancy, respiratory illness, neurological illness, inflammatory bowel disease, previous VTE, acute infection or heart failure. Records were excluded if the patient was admitted for VTE or to rule out VTE, receiving chronic anticoagulation, experiencing acute coronary syndromes, had a hospital stay ≤ 3 days, was a surgical or orthopedic patient, or pregnant. Data was collected on the timing of VTE related events for up to 100 days post discharge. Results: A total of 989 patients met criteria over the review period. Seventy-four percent (732/989) of all patients received mechanical or pharmacological prophylaxis in hospital. Only 2% (95% CI, 1.6% to 3.6%) of all patients received anticoagulation prophylaxis at discharge. Twenty-one percent of patients in the population studied were identified as requiring medical care for symptoms associated with VTE. Confirmation of VTE by diagnostic testing occurred in 4% (95% CI, 2.7% to 5.2%) while the other 17% (95% CI, 15.0% to 19.8%) had diagnostic tests that were negative or inconclusive. The mean length of time to confirmed first VTE event was 33.5 days. Eighty percent of first events occurred by day 57 and 90% of first VTE events occurred by day 69 post hospital admission. Patients with more than 2 risk factors had a rate of confirmed symptomatic VTE events of 6.1%, increasing to 8.7% for those with more than 3 risk factors while only 2.9% of patients with 2 or less risk factors developed a confirmed VTE. (p=0.015) Conclusion: This study demonstrates that in a real life setting, 6% of those hospitalized medical patients with more than 2 risk factors would develop symptomatic VTE event confirmed by diagnostic testing, increasing to 8.7% for those with more than 3 pre-specified risk factors. The mean time to first VTE event of 33.5 days along with 80% of VTE events occurring by day 57 suggest that more consideration needs to be given to prolonged VTE prophylaxis in this high risk population. The frequency and timing of the VTE events coupled with the results of the EXCLAIM study suggest that this high risk population may benefit from prolonged thromboprophylaxis. Disclosures: Hull: LEO Pharma: Consultancy; sanofi-aventis: Consultancy; Pfizer: Consultancy; Portola: Consultancy; Merck: Consultancy; Bayer: Consultancy; Johnson & Johnson: Consultancy. Merali:LEO Pharma: Consultancy; Genzyme: Consultancy; Boehringer Ingelheim: Consultancy; Abbott: Consultancy; BMS: Consultancy; Pfizer: Consultancy; Amgen: Consultancy; sanofi-aventis: Consultancy; Nycomed: Consultancy; Otsuka: Consultancy. Mills:Pfizer: Consultancy; sanofi-aventis: Research Funding. Komari:sanofi-aventis: Employment.
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 | 0,000 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».