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Enregistrement W3129064767 · doi:10.1093/milmed/usab048

On MoCAs and Bunker Pants

2021· article· en· W3129064767 sur OpenAlexaboutno aff
Meghan Quinn

Notice bibliographique

RevueMilitary Medicine · 2021
Typearticle
Langueen
DomaineComputer Science
ThématiqueDistributed systems and fault tolerance
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBunkerMedicineMedical emergencyGeographyArchaeologyCoal

Résumé

récupéré en direct d'OpenAlex

When I leave the hospital, I am not a physician. Or at least I do not identify as one. I define myself in a hundred other ways, but physician is not one of them. I think that comes from being a resident and, at times, lacking confidence in my ability to perform in my new role. After a month of working as the overnight psychiatry resident on call, I was familiar with delirium and capacity evaluations. I had done my share of Montreal Cognitive Assessments (MoCAs) and other cognitive assessments. But that night, I had a different job. I was staffing the heavy rescue truck at my volunteer rescue company, wondering what kind of exciting situations my overnight shift there might hold—a welcome change of pace from the psychiatry call room. When we were sent out for a lift assist, the scenario made famous by television ads for medical devices, I was not expecting much. It was the second time 911 had been called to the address that day. When we arrived, a middle-aged woman met us in the front yard, pleading for us to take her mother to the hospital, sharing a concerning series of events that stretched over the past several days. But then came the wrench—the patient did not want to go to the hospital. She refused. Earlier in the day, she had also refused and had been able to correctly identify the date, current president, and her current location, down to the zip code. That was enough evidence for the ambulance crew to trust her judgment and they had no choice but to leave her at home. It is hard enough to ensure a safe home environment for a patient when I am the consulting psychiatrist in a well-resourced hospital. However, here I was not acting in my role as a doctor. I was not in a hospital. I was a firefighter, and my patient was refusing the only care I could offer. At the daughter’s request, we entered the patient’s home, helped her off the floor, and then, just as I had done countless times as the psychiatrist on duty, began to listen to the patient. There were physical signs that concerned me about the patient’s ability to care for herself. But, just as she was earlier that day, she was appropriately oriented and conversant. While waiting for an ambulance crew to come and continue the evaluation, I listened. One of the benefits of psychiatry is the amount of time we are afforded to listen to our patients. I therefore tend to be more willing to listen to my rescue squad patients talk at length. This time, it turned out to be crucial. As we talked, the story and the timeline that emerged from the patient were vastly different from the story her daughter told us. None of it was overtly bizarre, but the details differed from the history the daughter had shared, and the more I pressed, the more obvious it became that the patient’s story was a complete confabulation. I found myself in familiar territory after all of those nights and delirium evaluations as a resident. I certainly do not carry the MoCA or Mini-Mental Status Exam in my bunker pants, a sharp contrast to always having several copies with me while on call, but I had done them enough recently to have parts of the evaluations memorized. Performing the parts of the test that evaluate attention such as serial 7’s and spelling “World” backwards gave me a lot of information about the patient’s cognitive state. It was not much information, but it was more than I could previously uncover. I knew what I would do in the hospital but this situation was different, as I was performing familiar work in a new territory. When the ambulance crew joined us, I gave my report and highlighted why the presentation was so concerning, then stepped back with my captain, and let the emergency medical technicians (EMTs) begin their evaluation. The back and forth stretched on for well over an hour, but the patient ultimately agreed to be transported to the local emergency room. As the patient was loaded into the ambulance and I climbed into the back of the rescue squad, I began to reflect on the experience. Almost 4 years previously, my experiences on the ambulance helped me figure out that psychiatry was the right specialty for me. In fact, my career as a volunteer firefighter and EMT helped guide me toward my current career in military medicine many times. I draw on my fire department experiences frequently when I am working with military patients in the hospital. I realized that for the first time, I was using my clinical experience in firefighting. In a small way, I was embracing my role and my identity as a physician. Montreal Cognitive Assessment—a cognitive screening test designed to assist health professionals in the detection of mild cognitive impairment and Alzheimer’s disease. Bunker gear, otherwise known as turnout gear, is the fire-resistant protective clothing worn by firefighters. The views expressed in this article are those of the author and do not necessarily reflect the official policy of the Department of Defense or the U.S. government. The author has no conflicts of interest to report.

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)0,001
score de la tête « metaresearch » (Gemma)0,007
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: aucune
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,059
Score d'incertitude au seuil0,199

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,007
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0040,002
Études des sciences et des technologies0,0010,001
Communication savante0,0010,002
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0590,036

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 Opus0,014
Tête enseignante GPT0,247
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
GenreÉditorial

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
Publié2021
Routes d'admission1
Résumé présentoui

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