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Enregistrement W4367835150 · doi:10.1097/eja.0000000000001827

The Autumn Ghost

2023· article· en· W4367835150 sur OpenAlexaboutno aff

Notice bibliographique

RevueEuropean Journal of Anaesthesiology · 2023
Typearticle
Langueen
DomaineArts and Humanities
ThématiqueShort Stories in Global Literature
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicine

Résumé

récupéré en direct d'OpenAlex

Hannah Wunsch Greystone Books; May 2023; 360 pages. ISBN-10: 1771649453 ISBN-13: 978-1771649452 When I was too young to understand what polio was, I was aware that it was something to fear. In my mind I carry an image of a child in an iron lung from a Hollywood film, and I recall being taken to the village school for a vaccine injection. This book tells a story of polio and the epidemic that ripped through Copenhagen in the early 1950 s, driving a revolution in medical care that is still evolving. Poliomyelitis is an infectious disease that waxed and waned throughout the first half of the 20th century. The population of the United States was at greatest risk in late spring and early summer, but in Scandinavia numbers peaked in the Autumn, where it was called the Autumn Ghost. Hannah Wunsch, a Canadian intensivist, weaves together the history of the disease, and the lives of the Americans and Danes who played their parts in its eradication, though what haunts the reader is the picture she paints of small blue faces, desperately struggling to get air into their lungs as they died. Clearly a great deal of research has gone into the book, with a wealth of personal detail that breathes life into the narrative. There are parallels with the Covid 19 pandemic everywhere, but then there was so much more ground to cover, and it took years. As with Covid, there were false starts, red herrings and disinformation, but the questions that needed answers were the same. The story moves smoothly back and forth through the years and between the USA and Denmark. The US, with its wealth had an abundance of iron lungs, but Denmark, emerging from years of Nazi occupation during the second world war, could afford only one. This imbalance led to an experiment with positive pressure ventilation to treat respiratory failure in Copenhagen. From this experience the intensive therapy unit was born. While there were many who made their contribution, it is the story of Bjorn Ibsen, the man who risked his reputation, that stands out. I was also very interested in the role of Poul Astrup, having been given an early Astrup machine for my first research project. If I had understood his pioneering genius then I would not have complained about having to recalibrate it every half an hour. Despite its title, it is written in American English, with American units. There were a couple of places where I itched for my editor's pencil, but this did not detract; the book is a good read. The story is illustrated by black and white photographs that add to the period atmosphere. I could not help being slightly shocked by the picture of the medical students in their white tunics, on their cigarette break. The book is intended for a wide readership. With this in mind, throughout the story there are explanations of some of the technical aspects of care. I was a bit sceptical about some of these at first, but then I read the author's explanation of a ‘blood gas’, that I thought was masterful, and decided the lay reader is in good hands. For those involved in anaesthesiology and intensive care there are many historical insights here that were new to me. This is not a text book, it is a story that would be worthy of reading even if there was no clinical connection. Read this and you will understand how intensive therapy was born. Gordon Lyons

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut 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: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,544
Score d'incertitude au seuil0,369

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,020
Tête enseignante GPT0,219
Écart entre enseignants0,199 · 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 tête enseignante, 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
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

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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