Implementation of an Emergency Medical Service integrated teleconsultation follow-up unit for home-based patients with suspected COVID-19 during epidemiological uncertainty in a island territory: Retrospective descriptive study (Preprint)
Notice bibliographique
Résumé
Background: Epidemiological and biological risks frequently expose Caribbean territories to emerging infectious threats. Martinique, a French overseas territory, is particularly vulnerable due to its tropical climate, insular geography, and recurrent exposure to arboviral epidemics. During exceptional health crises such as the COVID-19 pandemic, health care systems must rapidly adapt to a potentially sustained patient influx, evolving scientific knowledge, and heightened population anxiety. In March 2020, following the first confirmed COVID-19 cases in Martinique, the emergency medical service (EMS) implemented a teleconsultation follow-up unit dedicated to home-based patients with suspected SARS-CoV-2 infection, in the context of uncertainty regarding disease progression. Objective: This study aimed to evaluate the health and psychological impact of this EMS-based teleconsultation follow-up unit during the first COVID-19 wave, in order to assess its potential as an organizational response strategy for future infectious health emergencies. Methods: We conducted a single-center, retrospective, descriptive study including all adult patients monitored by the EMS COVID-19 teleconsultation unit during the first wave of the COVID-19 pandemic, between March 10 and May 31, 2020. Patients were initially triaged through the EMS call center and followed remotely using a standardized daily questionnaire. Follow-up frequency was determined according to clinical presentation. Collected data included sociodemographic characteristics, medical history, symptoms, polymerase chain reaction (PCR) testing status, clinical outcomes (recovery, hospitalization, or death), anxiety levels assessed using a 5-point Likert scale at the beginning and end of follow-up, and satisfaction measured on a 10-point numeric scale. Results: Among 1255 patients monitored during the study period, 908 met inclusion criteria (mean age 45, SD 17 years; 57.6% female). Most patients (n=724, 79.7%) had no prior medical history. The most frequently reported symptoms were fever (n=177, 19.5%), respiratory difficulties (n=165, 18.2%), cough (n=152, 16.7%), myalgia (n=114, 12.6%), and diarrhea (n=91, 10.0%). Only 10.6% of patients underwent PCR testing due to limited availability during the early epidemic phase, of whom 62.5% tested positive. During follow-up, 68 patients (7.5%) required hospitalization, and 2 (0.2%) died during their hospital stay. The presence of at least 1 pre-existing medical condition and older age were both significantly associated with hospitalization for suspected COVID-19 (P<.001). Among 590 respondents, mean anxiety scores decreased significantly from 3.9 (SD 0.8) at baseline to 1.4 (SD 1.1) at the end of follow-up, representing a 64.1% reduction (P<.001). Overall patient satisfaction with the teleconsultation service was high (mean score 8.7, SD 1.2, of 10). Conclusions: In the context of a novel epidemic with limited diagnostic and therapeutic knowledge, an EMS-integrated teleconsultation follow-up system enabled safe outpatient management while significantly reducing patient anxiety and preserving hospital resources. This approach may represent a scalable organizational model for maintaining access to care and supporting population reassurance during future infectious disease emergencies in geographically constrained or resource-limited settings such as small island territories.
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 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».