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Enregistrement W4244936578 · doi:10.1097/aln.0000000000003533

Stars

2020· article· en· W4244936578 sur OpenAlexaff
Christoph N. Seubert

Notice bibliographique

RevueAnesthesiology · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueCardiac, Anesthesia and Surgical Outcomes
Établissements canadiensAssembly of First Nations
Organismes subventionnairesnon disponible
Mots-clésMedicineUnconscious mindAnxietyMindsetAnestheticAnesthesiaSurgeryPsychiatryPsychoanalysisPsychology

Résumé

récupéré en direct d'OpenAlex

AS an anesthesiologist administering a general anesthetic, I perform the ultimate example of episodic care. The encounter is focused around one episode, one specific procedure in a patient’s life. The patient is unconscious for most of the encounter, reduced to a set of parameters on a monitor and mostly hidden under surgical drapes, while human structures are exposed and worked on that normally don’t see the light of day. Thus, it is easy to slip into production-line mode: the preanesthetic evaluation done by one person, intraoperative anesthesia care by another, and recovery by another yet. Such a production mindset can make light of the fact that for most patients, having an operation is understandable—at least on some level—whereas being under general anesthesia is not. A frequent response to an upcoming surgical procedure is concern about specific complications, whereas a typical response to an upcoming anesthetic is anxiety.“Your next patient is really cute,” the preoperative nurse tells me. Cute is not the first word that comes to mind as I prepare to see a small-for-age, developmentally delayed, 12-year-old with cerebral palsy in need of a revision of a ventriculoperitoneal shunt. I enter the preoperative bay to find a beaming boy, quite obviously not cowed by the difficult hand life has dealt him, accompanied by his friendly father. I sit on the boy’s stretcher, a little closer than a stranger should—intentionally—not only to talk at eye level, but also to gauge the boy’s response to strangers, knowing that what comes next will invade his space much more. He looks at me, interested—briefly—only to return to playing on the tablet computer in his hand. I ask the father how the boy handles procedures, given that many preceded this one. He likes to sing “twinkle, twinkle, little star” as he goes back for a procedure, his dad shares.“Your next patient is really cute,” I tell the nurse anesthetist I’m working with. She is a reserved person with more than two decades of clinical experience, who does not suffer fools gladly. “Yes, he is,” says the young operating room nurse. We go to pick up our patient. After a “See you later” from dad, the nurse begins “twinkle, twinkle, little star” and our group finds its pitch as we sing and travel in the long hallways of our Neuromedicine Hospital. Patient support technicians, the essential low-wage workers who keep our operating rooms stocked and clean, turn their heads as we pass by. After the briefing in the operating room, the nurse anesthetist gently places a face mask providing nitrous oxide over the boy’s nose and mouth. Under the stress of imminent events, the boy starts singing yet again. We join as sevoflurane is added to the inspired gas mixture. “Twinkle, twinkle, little star,” we sing, “and you’re off to space,” the nurse anesthetist says, noting the arrival of unconsciousness, “where stars don’t twinkle,” I say, ever the nerd. Why is that? Lack of atmosphere for refracting starlight. At the conclusion of the operation, we return a sleepy but comfortable boy to his father in the recovery room. As I return to the operating room to face my next task of the day, a patient support technician calls to me: “Hey, doc, I didn’t know you could carry a tune…”The production mindset in health care, which pushes us toward a state of perpetual preoccupation, also generates slogans used to advertise our work. Our slogan in neuromedicine is to “strive for the perfect patient experience.” Day after day we try, typically only to fall short, time and time again, for a frustratingly diverse and very human set of reasons. Sometimes, though, we get close. Humans caring for fellow humans. The tension between the production pressures, our patient’s humanity, and the humanity of those delivering care, resolved. All stars.

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)0,002
score de la tête « metaresearch » (Gemma)0,009
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: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,734
Score d'incertitude au seuil0,000

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,009
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,002
Études des sciences et des technologies0,0030,001
Communication savante0,0090,006
Science ouverte0,0020,004
Intégrité de la recherche0,0030,002
Charge utile insuffisante (le modèle a refusé de juger)0,7340,687

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 Opus0,030
Tête enseignante GPT0,263
Écart entre enseignants0,233 · 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
GenreAutre

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

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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