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Enregistrement W4414311971 · doi:10.4103/jets.jets_147_25

What’s New in Emergencies, Trauma, and Shock: Stroke Care as a Cycle; How Delays and Readmissions Drive Emergency Department Overcrowding

2025· editorial· en· W4414311971 sur OpenAlexaff
Siju V. Abraham, Jackie Bosch, Renyu Liu

Notice bibliographique

RevueJournal of Emergencies Trauma and Shock · 2025
Typeeditorial
Langueen
DomaineMedicine
ThématiqueEmergency and Acute Care Studies
Établissements canadiensHamilton Health SciencesMcMaster UniversityPopulation Health Research Institute
Organismes subventionnairesnon disponible
Mots-clésOvercrowdingEmergency departmentStroke (engine)MEDLINEEmergency medical services

Résumé

récupéré en direct d'OpenAlex

Emergency departments (EDs) have become the visible bottlenecks of modern health systems. However, multiple studies show that crowding is not caused by “lazy” physicians or bad triage, but by forces outside the ED – both upstream and downstream. For example, a recent U.S. study found that when hospital occupancy exceeded 85%, ED boarding times routinely surpassed the Joint Commission’s 4-h standard, with a median boarding time more than double what is seen during less crowded periods.[1] This excess time spent waiting for an inpatient bed traps patients on gurneys, diverts staff from other emergencies, and jeopardizes discharge planning. The study by Alhusain et al. reinforces this broader pattern: over one-fifth (22.2%) of stroke patients were back in acute care within 30 days of discharge, and one-third of these encounters were readmissions.[2] Such early returns to the ED after stroke discharge reflect a downstream “feed-back” into crowding just as surely as long boarding times; the study authors note that early outpatient follow-up significantly reduced acute care needs (50.3% of patients with the follow-up did not require additional acute care versus 30.9% without follow-up). However, the denominator may be underestimated, as patients discharged to inpatient rehabilitation were excluded – a subgroup who receive structured care but whose 30-day outcomes remain less clear. This nuance is important when interpreting the reported proportions. To break this vicious cycle, we must recognize that stroke care is a continuum that begins in the community long before the ED and continues after hospital discharge. DELAYS AT THE FRONT END Prehospital delays set the stage for ED strain. In many low- and middle-income countries (LMICs), public awareness of stroke symptoms is low, ambulance services are under-developed and access to imaging is limited.[3] In contrast, higher-income countries benefit from well-coordinated emergency medical services, widespread public education, and shorter door-to-needle times. The result is that many patients in the resource-limited settings present late, often with an established neurological disability that requires more intensive resources and longer ED stays – which further slows the queue for care. Stroke awareness alone is not enough – it must translate into actionable emergency response, or else it fails to mitigate these harmful delays.[4] Recent Indian data reinforce this picture: in a prospective cohort of 470 stroke patients, only 15.5% arrived within the 4.5-h thrombolysis window. Lack of awareness (odds ratio [OR] 5.16), absence of transport (OR 3.75), lower socioeconomic status, and longer distances from first medical contact to the ED were the strongest predictors of delay, while fewer than 5% used an ambulance and many first sought care at facilities without stroke capability.[5] The result is that many patients present late, with established disability requiring more resources and longer ED stays, which further slows the queue. OVERCROWDING AND RUSHED DISCHARGE: A SELF-REINFORCING LOOP Once EDs are full, clinicians face pressure to move patients through quickly. This can lead to abbreviated discharge instructions, inadequate medication counseling, improper referral, and follow-up information. In India, stroke survivors and caregivers report substantial unmet needs after discharge, with lack of information on warning signs, disability management, and rehabilitation services emerging as major barriers to recovery.[6] Without follow-up, two-thirds of acute care encounters were readmissions and 70% of patients returned to the ED.[2] They then return to the ED when complications arise, compounding crowding. This cyclical dynamic – delayed arrivals leading to crowding, crowding driving rushed discharges, and poor discharge planning leading to readmissions – points to the need for interventions across the entire continuum. In this study, nearly one-third of encounters were classified as “other”, a category that future research may help to clarify. BREAKING THE CYCLE FROM THE BEGINNING Experts convened by the World Stroke Organization (WSO) have emphasized that rapid recognition and transfer through emergency medical services is the most effective intervention.[7] Campaigns such as Stroke 120 (China), Stroke 911 (Mexico), and Stroke 112 (Nigeria) show how linking symptom recognition to emergency numbers can shorten onset-to-door times.[4] While technologies such as telemedicine, AI-assisted dispatch and portable diagnostics offer promise,[8] the WSO’s 2025 Scientific Statement makes clear that progress depends on nationally supported strategies combining awareness, workforce training, and affordable diagnostic tools – elements that still remain under-resourced in many LMICs.[9] DOWNSTREAM FIXES: DISCHARGE AND FOLLOW-UP Improving prehospital care will help reduce the number of late, severely affected patients in the ED, but it will not by itself eliminate crowding. Hospital leaders must also address the downstream side of the cycle. Discharge processes should start on the day of admission, with clear communication about medications, risk-factor management, and scheduled follow-ups. The Riyadh cohort emphasizes this point: patients who attended an early outpatient follow-up visit were far less likely to return for acute care, most often through the ED. The authors suggested barriers such as financial constraints, transport difficulties, low health literacy, and limited primary care, but these were not directly studied – and such challenges are likely to differ across regions, highlighting an important area for future research to guide locally adapted strategies. Postdischarge telephonic follow-up or home visits can reinforce self-care and catch problems early. Outpatient clinics need sufficient capacity to see stroke survivors promptly, because early follow-up visits are associated with significantly lower readmission rates. When patients receive timely follow-up, they are less likely to return to the ED with preventable complications, which eases pressure on overcrowded departments. CONCLUSION: A VIRTUOUS CYCLE Stroke care is a continuum. The decisions made by bystanders and dispatchers shape the severity of illness at ED arrival; while the quality of ED care and discharge planning influence how often patients return. The Riyadh study reinforces the cyclical logic – delays before arrival worsen crowding, crowding pressures discharges, and poor discharge planning drives readmission. By breaking the cycle at both ends – through public awareness and EMS strengthening upstream, and structured discharge and timely follow-up downstream – health systems can transform stroke care from a vicious circle into a virtuous one.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,033
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,031
Score d'incertitude au seuil0,062

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,033
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,004
Études des sciences et des technologies0,0030,003
Communication savante0,0090,014
Science ouverte0,0020,003
Intégrité de la recherche0,0030,004
Charge utile insuffisante (le modèle a refusé de juger)0,0050,001

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.

Tête enseignante Opus0,016
Tête enseignante GPT0,300
Écart entre enseignants0,285 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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