Response to Letter, “Risk of Venous Thromboembolism After Hospital Discharge in Patients With Inflammatory Bowel Disease”
Notice bibliographique
Résumé
We thank Dr. Dai and colleagues for their interest in our study, which compared the risk of venous thromboembolism (VTE) after hospital discharge in patients with inflammatory bowel disease (IBD) and in non-IBD control patients. We agree with the authors that the pathogenesis of VTE is multifactorial. One of the strengths of our study was our ability to control for a large number of variables that have been associated with VTE risk.1-3 Contrary to the authors’ assertion, we had a near-perfect match in baseline variables in our nonsurgical cohorts, based on our propensity score, including prior history of VTE and requirement for central venous catheters. Although there were subtle differences in age and comorbidities between our surgical cohorts, each of these variables was subsequently adjusted in our Cox proportional hazard models. Therefore, it is unlikely that differences in these variables accounted for our observations. Although the use of health administrative data has significant advantages, including the large sample size, the ability for longitudinal follow-up beyond hospitalization, and the availability of the full population of IBD patients in our region, there were limitations. The additional variables suggested by the authors as potential confounders were not available in our data. We were not able to determine clinical characteristics or genetic susceptibility. However, these were unlikely to have impacted our findings. For example, hereditary thrombophilia and other genetic variants associated with VTE are unlikely to differentially affect patients with IBD compared with non-IBD control patients. This result has been shown in a number of epidemiological studies where the rates of common genetic variants associated with VTE risk were comparable in patients with IBD and in the general population.4 Furthermore, fluid depletion during hospitalization is unlikely to directly impact VTE risk after hospital discharge given that fluid deficits are normally corrected before discharge. We acknowledge that there were a number of variables that we were unable to capture from our administrative data that may impact VTE risk, such as smoking and obesity. However, considering our population-based sample and matching of IBD patients and non-IBD control patients, it is unlikely that IBD patients would be at differential risk. Finally, we were unable to determine IBD severity or the use of medications, which are not available for all residents in our province. Although we agree with Dr. Dai and colleagues that these 2 variables have been associated with VTE,2,5,6 our study compared IBD patients with non-IBD control patients and was not designed to determine which factors were responsible for differences in the rates of VTE between these 2 populations. Conflicts of interest: JM reports consultancy fees and/or honoraria from Jannsen, AbbVie, Takeda, and Pfizer.
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 | 0,002 | 0,023 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,041 | 0,024 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,007 |
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 ».