S0623 Time Trends and Outcomes of Inter-Hospital Transfer in Patients With Upper Gastrointestinal Bleeding: A Nationwide Analysis
Notice bibliographique
Résumé
INTRODUCTION: Inter-hospital transfers occur commonly in clinical practice. However, outcomes in acute upper gastrointestinal bleed (UGIB) transfer patients have not been well described. Using a national database, we aimed to describe time-trends and outcomes in patients transferred to new hospitals with UGIB within the United States. METHODS: Adults with UGIB (defined using ICD-9 codes for acute variceal hemorrhage -AVH and acute nonvariceal hemorrhage-ANVH) were identified in the 2007-2014 National Inpatient Sample. Trends in inter-hospital UGIB transfers, along with patient and hospital-level descriptors were examined. Outcomes including all-cause in-hospital mortality, upper endoscopy (EGD) utilization, length of stay (LOS), and total hospital costs (THC) were also assessed after controlling for confounding variables. RESULTS: We identified 1,523,519 ANVH discharges of which 66,974 (4.3%) were transferred to a recipient hospital; 218,748 AVH discharges were identified of which 7,857 (9%) were transfers. Between 2007- 2014, there was a rise in AVH and ANVH transfers in the US (P = 0.02, Figure 1). The mean age at transfer was lower in AVH compared to ANVH (55 vs. 64 years) with the majority of transfer patients being White, on Medicare, and living below the median level of income [Table 1]. Twenty-seven percent of UGIB transfers occurred during the weekends, predominantly to teaching hospitals 71.9% (ANVH) and 79.9% (AVH). While 52% of ANVH transfers went to hospitals with a low/medium- volume of UGIB discharges, majority of AVH transfers went to high-volume hospitals (54.2%). In addition to poor UGIB outcomes, the adjusted odds of all-cause in-hospital mortality was significantly higher in transferred ANVH patients (adjusted Odds Ratio [aOR] 1.81, 95% Confidence Interval [C.I.] (1.52-2.14) and in transferred AVH patients (aOR = 1.44, 95% CI 1.52-2.1). EGD utilization was also significantly lower in transferred patients at their new hospitals where they had longer LOS and incurred higher hospital costs [Table 2]. CONCLUSION: Inter-hospital transfers for UGIB are on the rise in the US and these patients appear to be a vulnerable group with significantly lower odds of getting an EGD when they arrive recipient hospitals but with significantly higher adjusted odds of death, LOS, THC at the new hospitals. More research is needed to identify high-performing recipient hospitals to improve UGIB outcomes in this high-risk group.Figure 1.: Trends in inter-hospital transfer of acute non-variceal hemorrhage (ANVH) and acute variceal hemorrhage (AVH).Table 1.: Baseline demographics and comorbidity of inter-hospital transfer patients with acute non-variceal hemorrhage (ANVH) and acute variceal hemorrhage (AVH)Table 2.: Crude and adjusted odds ratio and mean ratios of outcomes of inter-hospital transfer patients with acute non-variceal hemorrhage (ANVH) and acute variceal hemorrhage (AVH)
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 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,006 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| 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 ».