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Enregistrement W2950773613 · doi:10.1213/ane.0000000000004262

Obstetric Anesthesia for Co-morbid Conditions

2019· article· en· W2950773613 sur OpenAlexaffabout
Kelly T. Au, Anthony Chau

Notice bibliographique

RevueAnesthesia & Analgesia · 2019
Typearticle
Langueen
DomaineMedicine
ThématiqueAssisted Reproductive Technology and Twin Pregnancy
Établissements canadiensBritish Columbia Centre of Excellence for Women's HealthUniversity of British ColumbiaB.C. Women's Hospital & Health Centre
Organismes subventionnairesnon disponible
Mots-clésObstetric anesthesiaMedicineAnesthesiologyPregnancyAnesthesia

Résumé

récupéré en direct d'OpenAlex

In recent years, advances in obstetric care have enabled women whose medical conditions would previously have precluded pregnancy to now successfully conceive and give birth. With an increasing prevalence of parturients presenting to the labor and delivery unit with pregnancy-related and preexisting comorbidities, there is a growing need for obstetric anesthesiologists to be equipped with broad and current knowledge of the range of medical conditions that can affect pregnant patients. Gunaydin and Ismail have attempted to fulfill this need through their new textbook, Obstetric Anesthesia for Co-morbidConditions. Both editors of this textbook are well-respected, well-qualified, and well-accomplished obstetric anesthesiology experts. Dr Gunaydin is Full Professor at the Department of Anesthesiology in Gazi University School of Medicine in Ankara, Turkey. She is the Chairman of the Obstetric Anesthesia Subcommittee in the Turkish Society of Anaesthesiology & Reanimation and has authored over 60 publications. Dr Ismail is Full Professor at the Aga Khan University in Karachi, Pakistan. In addition to many of her leadership roles and accomplishments in obstetric anesthesia, she started Pakistan’s first Obstetric Anesthesia Fellowship program in 2012 and became its founding director. This book is divided into 17 chapters, each highlighting a specific coexisting condition commonly seen in contemporary obstetric anesthesia practice followed by discussion of the impact they have on anesthetic management. The digital version of this book has an electronic search function, which makes it more portable and much easier to locate specific information compared to the print version. Overall, the authors have succeeded in delivering information that is concise, evidence-based, and relevant to clinical practice. The chapters are brief and succinct, allowing for fast reading cover to cover. The “key learning points” at the end of each chapter are effective in summarizing the salient information. The most unique topic in this book is the chapter by Yurtlu and Yurtlu on “Anesthesia for the Pregnant Patient with Intrathoracic Tumor.” Some chapters contain tables and figures that succinctly summarize the key messages. For example, the simple color diagram in Chapter 4 depicting how the combined spinal–epidural technique can confirm midline epidural placement provides much clarity to the text. However, most of the other chapters lack this important visual element. The motivation of learning and attention of the reader, particularly trainees, could be improved through more liberal use of color and illustrations, as well as more formatted, refined tables. There are some minor but obvious typographical errors. For example, in Chapter 5, reference 12 stated the year 2017 for a report from 2007. In Chapter 7, when discussing the fetal risk of excessive lowering of arterial partial pressure of carbon dioxide, the author stated “hypokalemia” when it should read “hypocarbia,” and mannitol dose of 0.5 mg/kg should read 0.5 g/kg. Some of the statements by the authors could benefit from further explanation and direct support from current literature. For example, in Chapter 3, epidural anesthesia is suggested to be preferable over spinal anesthesia for parturients with diabetes mellitus undergoing cesarean delivery; however, the use of spinal anesthesia in this population is common. In Chapter 8, awake fiberoptic intubation with local airway anesthesia is suggested as a method to help minimize increases in intracranial pressure for a parturient with Chiari malformation undergoing general anesthesia; however, more explanation is needed for readers to understand why an awake technique would be appropriate in this scenario. Finally, in Chapter 12, the recommended time intervals before and after neuraxial puncture for argatroban are different between the European Society of Anaesthesiology and American Society of Regional Anesthesia guidelines; special notations in the table to alert readers to discrepancies between the guidelines would be helpful. We believe that this is an excellent desk reference for both the experienced and occasional obstetric anesthesiologists who may encounter a parturient with a rare medical condition and wish to quickly refresh themselves with the essentials. This book would also be useful for the obstetric anesthesia trainee providers who have limited time but desire a contemporary and practical review of important comorbid conditions affecting pregnancy. For those who are seeking a comprehensive discussion or in-depth analysis of research theories and data, they may wish to supplement the reading with the classic title Chestnut’s Obstetric Anesthesia: Principles and Practice. Overall, Obstetric Anesthesia for Co-morbidConditions represents a basic, easy-to-read reference book for anesthesiologists caring for women with complex medical or pregnancy-related disorders who desire a concise clinical overview. Kelly Au, MD, FRCPCDepartment of AnesthesiaBC Women’s HospitalVancouver, British Columbia, Canada[email protected] Anthony Chau, MD, MMSc, FRCPCDepartment of Anesthesiology, Pharmacology and TherapeuticsUniversity of British ColumbiaVancouver, British Columbia, CanadaDepartment of AnesthesiaBC Women’s HospitalVancouver, British Columbia, Canada

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)0,004
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: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,032
Score d'incertitude au seuil0,105

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,004
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0010,003
Charge utile insuffisante (le modèle a refusé de juger)0,0320,018

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 Opus0,017
Tête enseignante GPT0,291
Écart entre enseignants0,274 · 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
GenreSynthèse

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

En bref

Citations1
Publié2019
Routes d'admission2
Résumé présentoui

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