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Record W2977860423 · doi:10.1111/acem.13865

<scp>Point of Care Ultrasound for Emergency Medicine and Resuscitation</scp>. <i>Edited by</i>PaulAtkinson, JustinBowra, TimHarris, BobJarman, and DavidLewis. New York: Oxford University Press, 2019; 264 pp; $90.00 (paperback).

2019· article· en· W2977860423 on OpenAlexaff
Daniel Kim

Bibliographic record

VenueAcademic Emergency Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicinePoint of care ultrasoundInferior vena cavaEmergency ultrasoundUltrasoundMedical emergencyRadiology

Abstract

fetched live from OpenAlex

Point of Care Ultrasound for Emergency Medicine and Resuscitation is the latest entry to the current plethora of point-of-care ultrasound (POCUS) books in acute care medicine. The editors are all experienced emergency physicians who were early adopters of bedside ultrasound and have used their expertise to become international leaders in POCUS. This text is a basic introduction to POCUS that is most relevant to emergency physicians, but it will appeal to any physician practicing acute care medicine, including critical care, internal medicine, hospital medicine, and pediatrics. After an introduction to the concept of POCUS and ultrasound physics and knobology, the subsequent seven chapters are organized into anatomic organ systems: heart (echocardiography), chest (thoracic), abdomen (free fluid, biliary, renal, bowel obstruction, appendicitis), pelvis (early pregnancy), vascular (aorta, inferior vena cava, deep vein thrombosis), musculoskeletal, and small parts (ocular and scrotal). This is followed by a chapter on procedural guidance. The last three chapters cover ultrasound in specialized environments: education and simulation, pediatrics, and lastly, prehospital care. Overall, it is logically and intuitively organized, and it is easy to find the chapter covering the ultrasound application one wants to review. However, the chapter on education and simulation is awkwardly inserted between chapters covering clinical POCUS applications. Grouping all the clinical chapters together would improve the flow of the book; the nonclinical chapters could then round out the end of the text. The authors do a good job of breaking down POCUS applications into core and advanced, based on difficulty of mastery and clinical utility. Each chapter starts with a brief half-page summary highlighting the clinical indications, important key points, and clinical utility of the scans covered in the chapter. Not only is this an excellent introduction to each chapter, but it’s also a great way to quickly review the chapter afterward. Specific POCUS applications are organized into subsections: image generation, image interpretation, pitfalls, and clinical use. The ultrasound novice will find these sections easy to navigate. This text also attempts to be as evidence based as possible, referring to literature and studies published as recently as 2018. Each chapter concludes with a “further reading” section that lists important studies, guidelines, and review articles. By referencing the evidence base, the reader gains a better understanding of the strengths and limitations of POCUS. One also learns some interesting esoteric details, such as the fact that “the disappearance of lung sliding in pneumothorax was first described in horses.” As a bonus, the education and simulation chapter provides a good review of the current state of POCUS training among different specialty organizations and a framework for POCUS curriculum development. However, there are some issues with this book. It covers the heart, chest, and abdomen chapters in extensive detail, including advanced echocardiographic topics like regional wall motion abnormality, diastolic function, and stroke volume calculation. Yet other topics like skin and soft tissue infection, joint effusion, scrotal, airway, intussusception, and pyloric stenosis are covered in a superficial manner. The procedures chapter could be improved by including a subsection on indications and contraindications for each procedure. While the first chapter contains clinical vignettes demonstrating the utility of POCUS, it would be helpful for each chapter or application to have its own illustrative clinical case. Stylistically, the writing is in the Queen’s English, using terms like “right iliac fossa” rather than “right lower quadrant.” Finally, the book suffers from a lack of consistency in both its illustrations and ultrasound images. The illustrations and figures seem to be sourced from a variety of different illustrators and publications. Furthermore, while most ultrasound images are from actual patients, some ultrasound images are sourced from a Vimedix ultrasound simulator (CAE Healthcare). Ultrasound is a visual modality, so this lack of consistency and cohesiveness in the book’s images is distracting. Despite these minor issues, Point of Care Ultrasound for Emergency Medicine and Resuscitation is a welcome addition to the POCUS library and a great resource for the beginner. I would recommend this book to residents and physicians who have limited ultrasound experience or knowledge, because it provides a solid foundation and introduction to the broad variety of POCUS applications available to the acute care provider.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.295
Threshold uncertainty score0.986

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.2950.242

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.044
GPT teacher head0.330
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2019
Admission routes1
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