Outcomes of Telestroke Inter-Hospital Transfers Among Intervention and Non-Intervention Patients
Notice bibliographique
Résumé
Background: Telestroke is an established telemedicine method of delivering emergency stroke care. However, not all neurological patients utilizing telestroke service require emergency interventions or transfer to a comprehensive stroke center. To develop an understanding of the appropriateness of inter-hospital neurological transfers utilizing the telemedicine, our study aimed to assess the differences in outcomes of inter-hospital transfers utilizing the service in relation to the need for neurological interventions. Methods: The pragmatic, retrospective analysis included 181 consecutive patients, who were emergently transferred from telestroke-affiliated regional medical centers between October 3, 2021, and May 3, 2022. In this exploratory study investigating the outcomes of telestroke-referred patients, patients receiving interventions were compared to those that did not following transfer to our tertiary center. Neurological interventions included mechanical thrombectomy (MT) and/or tissue plasminogen activator (tPA), craniectomy, electroencephalography (EEG), or external ventricular drain (EVD). Transfer mortality rate, discharge functional status defined by modified Rankin scale (mRS), neurological status defined by National Institutes of Health Stroke Scale (NIHSS), 30-day unpreventable readmission rate, 90-day clinical major adverse cardiovascular events (MACE), and 90-day mRS, and NIHSS were studied. We used X 2 or Fisher exact tests to evaluate the association between the intervention and categorical or dichotomous variables. Continuous or ordinal measures were compared using Wilcoxon rank-sum tests. All tests of statistical significance were considered to be significant at P < 0.05. Results: Among the 181 transferred patients, 114 (63%) received neuro-intervention and 67 (37%) did not. The death rate during the index admission was not statistically significant between the intervention and non-intervention groups (P = 0.196). The discharge NIHSS and mRS were worse in the intervention compared to the non-intervention (P < 0.05 each, respectively). The 90-day mortality and cardiovascular event rates were similar between intervention and non-intervention groups (P > 0.05 each, respectively). The 30-day readmission rates were also similar between the two groups (14% intervention vs. 13.4% non-intervention, P = 0.910). The 90-day mRS were not significantly different between intervention and non-intervention groups (median 3 (IQR: 1 - 6) vs. 2 (IQR: 0 - 6), P = 0.109). However, 90-day NIHSS was worse in the intervention compared to non-intervention group (median 2 (IQR: 0 - 11) vs. 0 (IQR: 0 - 3), P = 0.004). Conclusions: Telestroke is a valuable resource that expedites emergent neurological care via referral to a stroke center. However, not all transferred patients benefit from the transfer process. Future multicenter studies are warranted to study the effects or appropriateness of telestroke networks, and to better understand the patient characteristics, resources allocation, and transferring institutions to improve telestroke care. J Clin Med Res. 2023;15(6):292-299 doi: https://doi.org/10.14740/jocmr4945
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 | 0,004 |
| 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 | 0,001 |
| Science ouverte | 0,000 | 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 ».