37 Accessible and Specialized COVID-19 Testing for Children and Youth with Medical Complexity
Notice bibliographique
Résumé
Abstract Background COVID-19 testing for symptomatic individuals is a key public health measure for infection prevention and control. However, COVID-19 testing can be uncomfortable without appropriate supports and can lead to testing hesitancy amongst certain populations such as children with medical complexity (CMC) and those with underlying neurological and respiratory conditions. To support COVID-19 testing, a specialized initiative was developed for CMC and their families onsite at The Hospital for Sick Children to enhance testing uptake, reduce barriers to access, and support a safe and accommodated testing environment for families. Multiple modalities of testing were involved and could be completed in their personal vehicle, with specialized support from nurses and child life if needed. Objectives The objectives of our study were to investigate the characteristics of CMC and their families who underwent COVID-19 testing through our program, evaluate indications for testing, and collect case positivity rates. Design/Methods Prospective data, including testing and population characteristics, were collected from December 2020-August 2021 through a centralized system, and was analyzed using descriptive methods. Results 335 children (Table 1) with medical complexity came to the COVID-19 Assessment Center for testing. Of those who were tested 88% (294) had neurodevelopmental conditions with highly challenging behaviours (e.g. autism, developmental delay), and 12% (28) were classified as CMC (i.e. those with active use of medical technology e.g. tracheostomy, G-tube etc.). Of those tested, 6% (21) tested positive for COVID-19. Sixty percent (199) were tested due to having symptoms consistent with COVID-19, 27% (90) had a COVID-19 exposure, 8% (26) were exposed and tested as part of outbreak management and 5% were of an unknown criteria. The majority of completed tests (74%) were nasopharyngeal (NP) swabs, 18% completed saliva tests and 6% completed anterior nares/throat swab tests. Thirteen percent (43) of families requested additional supports such as extra nurses, child life specialists or other accommodations. All patients had a dedicated paediatric nurse and received testing in their personal vehicle. Conclusion CMC and their families face unique barriers to COVID-19 testing. A specialized testing centre for CMC was able to support families by providing unique opportunities for testing, revealing a 6% COVID-19 positivity rate. NP swabs that can be painful were supported through in-vehicle testing with dedicated pediatric nurses. Robust health and safety measures, including a coordinated testing approach, are necessary to ensure accessible testing opportunities for CMC and their families. Further research is needed to be able to support this unique population.
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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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».