Evidence map›Paper›PMID 38216208›Full record

ArticleFamily medicine and community health2024

COVID-19 patient experiences in prehospital pathways: a processual approach using life-events calendar method and state sequence analysis shows detrimental delays.

Romain Lutaud, Sebastien Cortaredona, Lea Delorme, Patrick Peretti-Watel, Juliette Mirouse, Manon Borg, Lucie Cattaneo, Didier Thery, Gaetan Gentile, Christian Pradier and 5 more

Open access · diamondAbstract read
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Article in Family medicine and community health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 42% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 7 institutions in 2 countries.

Romain LutaudDepartment of General Practice, Aix-Marseille University, Marseille, France romain.lutaud@univ-amu.fr.ORCID 0000-0003-3443-5937
Sebastien CortaredonaInstitut de Recherche pour le Développement (IRD), Marseille, France.
Lea DelormeAssistance Publique- Hôpitaux de Marseille (AP-HM), Marseille, France.
Patrick Peretti-WatelINSERM, Marseille, France.
Juliette MirouseDepartment of General Practice, Aix-Marseille University, Marseille, France.
Manon BorgDepartment of General Practice, Aix-Marseille University, Marseille, France.
Lucie CattaneoAssistance Publique- Hôpitaux de Marseille (AP-HM), Marseille, France.
Didier TheryDepartment of General Practice, Aix-Marseille University, Marseille, France.
Gaetan GentileDepartment of General Practice, Aix-Marseille University, Marseille, France.
Christian PradierDepartment of Public Health, Archet University Hospital, Nice, France.
Touitou IritDepartment of Public Health, Archet University Hospital, Nice, France.
Philippe BrouquiMEPHI, Marseille, France.
Sophie TardieuCEReSS - Health Service Research and Quality of life Center, Marseille, France.
Michel CarlesDepartment of Infectious Diseases, Centre Hospitalier Universitaire de Nice, Nice, France.
Stéphanie GentileCEReSS - Health Service Research and Quality of life Center, Marseille, France.
Aix-Marseille Université · FRMéditerranée Infection Foundation · FRCentre Hospitalier Universitaire de Nice · FRCeres · USAssistance Publique Hôpitaux de Marseille · FRInserm · FRInstitut de Chimie de Nice · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo our best knowledge, no study in France has comprehensively investigated the prehospital history of patients admitted for severe cases of COVID-19. 'Patients' voice is an excellent means to capture data on primary care pathways.We aimed to identify clusters of COVID-19 hospitalised patients with similar prehospital symptom sequences, and to test whether these clusters were associated with a higher risk of poor clinical outcomes.

designCross-sectional online survey using life-event calendars.

settingAll patients hospitalised for COVID-19 between September 2020 and May 2021 in the Infectious Disease Departments in Nice and in Marseilles in France.

participants312 patients responded to the survey.

main outcome measuresFrom the day of symptom onset to the day of hospitalisation, we defined a symptom sequence as the time-ordered vector of the successive symptom grades (grade 1, grade 2, grade 3). State sequence analysis with optimal matching was used to identify clusters of patients with similar symptom sequences. Multivariate logistic regressions were performed to test whether these clusters were associated with admission to intensive care unit (ICU) and COVID-19 sequelae after hospitalisation.

resultsThree clusters of symptom sequences were identified among 312 complete prehospital pathways. A specific group of patients (29%) experienced extended symptoms of severe COVID-19, persisting for an average duration of 7.5 days before hospitalisation. This group had a significantly higher probability of being admitted to ICU (adjusted OR 2.01). They were less likely to know a loved one who was a healthcare worker, and more likely to have a lower level of education. Similarly, this group of patients, who were more likely to have previously visited the emergency room without exhibiting severe symptoms at that time, may have been inclined to postpone reassessment when their health worsened.Their relatives played a decisive role in their hospitalisation. CONCLUSION AND RELEVANCE: This study highlights the negative impact of delayed hospitalisation on the health outcomes of French patients with severe COVID-19 symptoms during the first wave and underscores the influence of socioeconomic factors, such as lower education levels and limited connections to the medical field, on patients' experiences.

Indexed as

COVID-19Emergency Medical ServicesCross-Sectional StudiesHumansPatient Outcome AssessmentSARS-CoV-2COVID-19Patient NavigationPrimary Health Care

Identifiers

PMID38216208
PMCPMC10806557
OpenAlexW4390820761

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.