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Enregistrement W2971039575 · doi:10.1373/jalm.2019.029439

Challenges of Point-of-Care Testing in Ambulances

2019· article· en· W2971039575 sur OpenAlexaff
Anna K. Füzéry, Jason Bobyak, Eddie L. Chang, Robert S. Sharman, Allison A. Venner

Notice bibliographique

RevueThe Journal of Applied Laboratory Medicine · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueCardiac Arrest and Resuscitation
Établissements canadiensUniversity of CalgaryUniversity of Alberta
Organismes subventionnairesnon disponible
Mots-clésPoint-of-care testingPoint (geometry)MedicineMathematics

Résumé

récupéré en direct d'OpenAlex

Many countries rely on hospitals to provide the majority of their emergent and critical care. However, this healthcare delivery model is imperfect and leads to overcrowding, excessive wait times, and delays in diagnosis and treatment. Moreover, certain patients, such as those living in rural areas, may not be able to access timely hospital-based care at all. Healthcare organizations are, therefore, increasingly exploring ways to begin care during the initial medical encounter and before arriving at the hospital (1). A popular paradigm for this is the provision of emergent and critical care by ambulances. For example, Alberta relies on air ambulances, traditional ground ambulances, and a stroke ambulance to provide life-saving care to seriously ill or injured patients before they reach a hospital. Ambulance services may exist in much more limited capacity elsewhere, but they still have significant potential to accelerate and improve care in emergent situations. Ambulances in resource-rich settings frequently carry onboard 1 or more point-of-care testing (POCT) systems. It is widely believed that these systems provide value to patient care, but how does one actually confirm this? Before POCT implementation, a careful needs assessment should be carried out to identify any deficiencies and to assess the potential of POCT to help address them (2). This assessment should then be further supplemented by a cost analysis that includes the following: (a) purchase and validation of POCT systems, quality assurance materials, and any additional supplies; (b) ambulance modifications necessary to accommodate POCT; (c) end user education and training; (d) initial and ongoing support by a POCT expert; (e) any additional considerations that may exist. At times, it can be difficult to gather such evidence owing to limited resources, the challenges of studying critically ill patients, and an incomplete understanding of POCT quality assurance requirements. Nevertheless, this evidence reveals the true value of POCT and enables informed decision-making and responsible resource allocation (3). Vehicle design is an additional important consideration in ambulance-based POCT. Every vehicle must have certain basic features to achieve a minimum level of accuracy and safety with respect to POCT (Table 1). Improvements beyond these may enable more complex POCT to be performed and, thereby, the provision of more complex care. However, those considering POCT in their ambulances should be forewarned that meeting the basic features noted in Table 1 can be challenging even in otherwise advanced vehicles. For example, we are still working on an effective solution to protect POCT systems in the Alberta Stroke Ambulance and Shock Trauma Air Rescue Service helicopters from transient exposures to winter temperatures of −10 °C to −20 °C (14 °F to −4 °F). Such exposure not only leads to device inoperability during potentially critical situations but may also affect result accuracy in ways that are incompletely understood (4). Important vehicle design features to enable ambulance-based POCT. Important vehicle design features to enable ambulance-based POCT. Technological advancements in POCT may alleviate some of the previously discussed challenges (5). Test consolidation into clinically relevant panels and onto 1, or at most 2, compact POCT devices can reduce space requirements significantly. Successful examples of this include panels for electrolyte disturbances, blood gas disorders, and acid–base imbalances. Similar approaches could be taken for other emergent conditions such as certain pregnancy complications, hyperglycemic crises, sepsis, and stroke. Panels should include all biomarkers essential to care and those that show strong promise for clinical adoption in the next few years. The formulation of more robust reagents can also ameliorate space usage, along with improving result accuracy and reagent usage. Reagents that remain stable at room temperature for several months free up refrigerator space for other temperature-sensitive materials or eliminate the need for a refrigerator altogether. Reagents that degrade minimally from repeated, transient exposure to extremes of temperature, humidity, and/or pressure enable result accuracy to be maintained over a longer timeframe and avoid the need to replace reagents before their manufacturer-stated expiry date. Lastly, POCT in ambulances must be fully compliant with local and national regulations. This requirement can pose a significant barrier to POCT adoption because there may not be any suitable systems approved for use in this setting. For example, the Alberta Stroke Ambulance relies on the Sysmex pocH-100i hematology analyzer for platelet counts. A similar system, the Sysmex XW-100 hematology analyzer, recently received approval for point-of-care use in the US but only for ambulatory general practitioner's offices. To increase emergent and critical care in ambulances, regulatory changes may be necessary to allow use of POCT on all patients with a certain clinical status regardless of their physical location.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,039
score de la tête « metaresearch » (Gemma)0,089
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,039
Score d'incertitude au seuil0,208

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0390,089
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0020,005
Communication savante0,0060,007
Science ouverte0,0060,005
Intégrité de la recherche0,0050,006
Charge utile insuffisante (le modèle a refusé de juger)0,0130,006

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.

Tête enseignante Opus0,019
Tête enseignante GPT0,281
Écart entre enseignants0,261 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations9
Publié2019
Routes d'admission1
Résumé présentoui

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Même revueThe Journal of Applied Laboratory MedicineMême sujetCardiac Arrest and ResuscitationTravaux en français237 207