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)
Bibliographic record
Abstract
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".