Cohort profile: A multicenter evaluation of clinical decision rules applied to emergency department triage of patients presenting with acute respiratory infection or infectious diarrhea
Notice bibliographique
Résumé
ABSTRACT Purpose Emergency department (ED) patients suffering from acute respiratory infection or infectious diarrhea often present with self-limiting conditions. The study objective was to evaluate the performance of triage clinical decision rules consisting of a rapid molecular test and a self-administered patient questionnaire to identify ED patients who can self-treat at home without consulting an emergency physician. This article describes the profile of the cohorts recruited. Participants Participants were prospectively recruited in 4 EDs in Québec City and Montréal, Canada, from February 2022 through March 2023. Participants were aged ≥18 years, had an acute respiratory infection and/or acute infectious diarrhea, and had received a Canadian Triage and Acuity Scale score between 3 (urgent) and 5 (non-urgent). Participants were asked to complete a self-administered risk stratification questionnaire after triage and to follow usual ED care afterward. Nasopharyngeal and/or rectal swabs were collected and frozen for subsequent testing on a rapid molecular testing device. Data were obtained during the recruitment visit, during a follow-up phone call 7 days later and from medical records. The primary outcome to be predicted by the clinical decision rules was an aggregation of hospitalization, return visit and mortality at 7 days. Findings to date We recruited 1,391 participants, 62.3% of whom were women, 80.7% were aged under 60, 78.2% had no comorbidities, 76.5% presented with an acute respiratory infection, 17.8% with an acute infectious diarrhea and 5.7% with both. Hospitalization and return visits incidence proportions at 7 days were respectively 10.8% and 13.1% for respiratory infections and 14.1% and 16.5% for infectious diarrhea. No death was recorded. Future plans The data gathered from these cohorts will enable us to test, refine, derive, and validate clinical decision rules used to help ED triage nurses offer the most suitable care to patients presenting with acute respiratory infections or infectious diarrhea. Strengths and limitations Our study has both strengths and limitations. Among the strengths: The cohorts were recruited from 4 different EDs and reached the target sample size for acute respiratory infections and acute infectious diarrhea. The potential economic impact of the clinical decision rules will be assessed from the perspective of both the health system and the patient. The main limitations are the following. Cohorts were recruited by convenience sampling and may not be representative of the entire ED population. The patient self-administered questionnaires used in this study were derived from systematic reviews and rapid prototyping, but not according to the methodological standards recommended for the derivation of clinical decision rules. However, the study dataset was built to enable rules to be refined and if necessary, new rules to be derived and internally validated. We recorded a 12.9% loss of participants at the 7-day follow-up phone call. However, the primary outcome measures (return visits, admissions and deaths) will be obtained from provincial administrative databases. These reliable data will enable us to overcome this limitation for future projects to refine and validate robust triage clinical decision rules.
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 | 0,021 | 0,040 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| 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) | 0,001 | 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 ».