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Enregistrement W1525481820 · doi:10.1093/pch/11.4.209

Routine vital signs not so routine: Next question? When does it matter?

2006· article· en· W1525481820 sur OpenAlexaff
David McGillivray

Notice bibliographique

RevuePaediatrics & Child Health · 2006
Typearticle
Langueen
DomaineMedicine
ThématiqueEmergency and Acute Care Studies
Établissements canadiensMontreal Children's Hospital
Organismes subventionnairesnon disponible
Mots-clésVital signsMedicineIntensive care medicineSurgery

Résumé

récupéré en direct d'OpenAlex

Vital signs at triage are under close scrutiny these days. It makes for interesting reading because vital signs measurement has always been believed to be an essential component of paediatric patient triage in the emergency department. Throughout our training, we are continually told that vital signs are the bread and butter of patient assessment. Despite the perceived importance of vital signs, Gravel et al, in this issue of Paediatrics & Child Health (pages 211–215), show us clearly that “routine vital signs” are not necessarily routine in a large paediatric tertiary care centre. Similar findings have been reported in other studies, as acknowledged by the authors, and I suspect their results are generalizable to many more paediatric and general emergency departments across North America. New information shown by Gravel et al is that whether vital signs are taken at triage may not be based on issues related to the patient. They have shown that the presence or absence of vital signs data varies significantly based on the time of presentation to the emergency department: vital signs data are less likely to be documented for patients arriving during evening shifts. The absence of vital signs data did not appear to correlate with increased emergency waiting times to triage. It is hard to know whether nurses changed their standard triage routine on the basis of a visual knowledge of the number of patients waiting to be triaged and then abbreviated their routine, or whether there were other factors, such as increased nurse experience on the evening shifts. What the paper does not tell us is whether there were consequences to not documenting vital signs data for these children. Cooper et al (1) discussed the effect of vital signs data on triage decisions in a population of 14,285 patients, including 1050 children younger than two years. In that study, vital signs measurements taken on the same patient after the patient had been triaged without vital signs measurements changed the triage assignment in 11.4% of patients. Triage assignment was more likely to be changed to a more severe category than to a less severe category. The ultimate dispositions (eg, admission to hospital) showed a stronger correlation with the revised triage category than with the initial triage category. Salk et al (2) examined the influence of vital signs data on triage assignment. They found that vital signs data changed triage assignment in 5.7% of patients, again showing a tendency to change to a more severe category. Their result, however, was not significant. A special concern with paediatric vital signs, obtained at triage, is their accuracy. Many vital signs are now measured electronically with the exception of respiratory rate. Most of the electronic equipment, such as the automated blood pressure and heart rate monitor, work very well in critically ill adult or paediatric patients who lay very still due to their illness. They do not work well in the uncooperative but conscious paediatric patient at triage. Measuring an accurate respiratory rate is often very difficult, as is shown in a study by Lovett et al (3), in which neither clinical assessment nor an electronic monitor gave an accurate respiratory rate at triage. Poor accuracy of vital signs measurements has the potential to lead to misclassification of the patient's triage category and to unnecessary investigations. This may be worse than if no vital signs had been measured. There are many things in medicine that we do as a part of a routine. Sometimes, when things become routine, we may miss the significance or importance of the measurement. As with most things, it is always valuable to re-evaluate dogma and make sure that what we do makes a positive difference for the well-being of the patients. Vital signs at triage are a good place to start. When assessing the value of vital signs measurements at triage, we need to use the same rigour that we use to evaluate other diagnostic tests. Tests must be practical, reproducible, responsive to change, valid, discriminatory and have good interobserver agreement. We need to look at the sensitivity, specificity and likelihood ratios of tests to determine whether they will be useful in helping the triage nurse sort out which patients are likely to have a significant medical or surgical problem. In times of decreasing resources, both financial and human, we cannot afford to do unnecessary procedures or tests. We need to consider the harm done by false-negative and false-positive results. At this time, it remains unclear whether all patients arriving at triage need a complete set of measurements of the five paediatric vital signs (heart rate, respiratory rate, temperature, blood pressure and oxygen saturation). The difficult scientific challenge is to determine who needs what vital signs measured and who does not based on the potential clinical impact on the patient. We will always need a dose of common sense and experience to help us make these decisions as we sit in front of the patient.

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)0,016
score de la tête « metaresearch » (Gemma)0,171
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,016
Score d'incertitude au seuil0,084

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0160,171
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,006
Communication savante0,0060,010
Science ouverte0,0020,002
Intégrité de la recherche0,0120,013
Charge utile insuffisante (le modèle a refusé de juger)0,0160,008

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 Opus0,011
Tête enseignante GPT0,283
Écart entre enseignants0,271 · 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'étudeSans objet
Domainenon disponible
GenreCommentaire

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

En bref

Citations6
Publié2006
Routes d'admission1
Résumé présentoui

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