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Record W2753278150 · doi:10.1213/ane.0000000000002340

Obstetrics and Gynecology in Low-Resource Settings: A Practical Guide

2017· article· en· W2753278150 on OpenAlexaffabout
Ronald B. George

Bibliographic record

VenueAnesthesia & Analgesia · 2017
Typearticle
Languageen
FieldMedicine
TopicGlobal Health and Surgery
Canadian institutionsIzaak Walton Killam Health Centre
Fundersnot available
KeywordsMedicineObstetrics and gynaecologyOutreachHealth careResource (disambiguation)Medical educationNursingFamily medicinePregnancyEconomic growth

Abstract

fetched live from OpenAlex

Dissemination of high-quality medical knowledge to areas of low resources is critical to the care of millions of people. Obstetrics and Gynecology in Low-Resource Settings: A Practical Guide delivers on its goal to provide evidence-informed practical guidance to care providers working in low-resource countries. The editor of the book, Dr Nawal M. Nour, gives readers practical management strategies for problems faced in low-income countries: human immunodeficiency virus–complicated pregnancy, obstetric fistula, unsafe abortions, violence against women, and anesthesia-related morbidity. These topics are important to an anesthesiologist who plans to work in a low-resource environment. Dr Nour is director of the Division of Global Obstetrics and Gynecological Health at Brigham and Women’s Hospital in Boston, Mass, and associate professor at Harvard Medical School. She established the African Women’s Health Center, which focuses on care for women who have undergone female genital mutilation. The African Women’s Health Center also provides outreach programs to the African community in Boston. Nour wrote this book to “present an epidemiologic picture of their subject and practical approaches to treating real-world patients.” Dr Nour lends her expertise to chapter 11, “Female Genital Cutting.” I have been an active participant in a number of global health efforts to improve anesthesia conditions and to help organize a meeting to prepare anesthesiologists working and educating in low-resource environments. For this reason, I had a strong appreciation for the sections written by Nour: “Are You Doing This for the Right Reasons?”; “Is Global Health Right for You?”; and “How Do You Fit Into the Picture of Global Women’s Health?” These sections enticed me to reflect on my own motivations; as Nour says, “improving the health and well-being of women worldwide is worth the effort.” The chapter titled “Maternal Mortality in Low-Resource Countries” was another highlight for me. Lalonde and Miller provide readers with a well-indexed history of the struggle to reduce maternal mortality worldwide. They discuss the unsurprising major causes of maternal mortality and practical considerations, but they also provide readers with observations on how we may continue to reduce the direct causes of maternal mortality. Part IV of the book comprises 2 chapters focusing on the teamwork challenges of obstetric and gynecology practice in low-resource environments. In Chapter 13, Dinesh Jagannathan and Bhavani Kodili describe a detailed picture of what it is like to provide anesthesia in these environments and the importance of safe anesthesia to reduce maternal and newborn mortality. They emphasize the need for essential equipment, drugs, protocols, and, perhaps most important, well-trained anesthesia providers. This chapter illustrates the benefits of educational initiatives developed by nonprofit organizations to enhance the safety of anesthesia for childbirth. In Croatia, the nonprofit organization Kybele provided a program of education for cesarean delivery anesthesia that increased the use of regional anesthesia from 18% to 59%.1 It also highlights the anesthesia fellowship training programs from the World Federation of Societies of Anaesthesiologists and their web-based educational programs.2 The chapter on anesthesia for childbirth provides a necessary summary of the limitations of monitoring, medication, transfusion medicine, and anesthesia equipment that affect clinicians in low-resource environments. Jagannathan and Kodili also provide readers with practical protocols for the management of women’s care during childbirth. These include protocols for neuraxial and general anesthesia for cesarean delivery, as well as postoperative pain management. They adapted a World Health Organization reference table (Table 13.1) to describe the minimum requirements for the provision of obstetric anesthesia. There is also a concise section on labor analgesia. Neuraxial labor analgesic techniques are used infrequently in low-resource environments, and are often overlooked in many texts regarding anesthesia care in low-resource environments. Jagannathan and Kodili briefly mention nonneuraxial aspects of labor analgesia, including parenteral opioids and nitrous oxide. My personal experience might suggest a need to expand on labor analgesia in future editions. As an obstetric anesthesiologist who has worked alongside local clinicians in many low-resource environments, I would recommend this book to colleagues and students who have worked or are planning to work in these challenging environments. I believe this book has value in providing greater insight to anesthesiologists working as part of a global health mission that targets maternal and newborn health. We are rarely involved with isolated obstetric anesthesia projects in low-resource environments. It is important for us to recognize some of the problems faced by our obstetrician teammates to improve how we work alongside one another. In the current era, I hope a digital version will be available for easy access and transportability. The practical aspects of this book will be of value to friends working in low-resource environments. My own copy is now packed in my travel bag, both for review during a long flight and to pass forward to a global health colleague on my next trip abroad. Ronald B. George, MD, FRCPCDepartment of Women’s & Obstetric AnesthesiaIWK Health CentreHalifax, Nova Scotia, Canada[email protected]

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)0.002
metaresearch head score (Gemma)0.007
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: Other · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0030.005
Open science0.0020.003
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0380.037

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 head0.018
GPT teacher head0.321
Teacher spread0.302 · 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
GenreOther

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
Published2017
Admission routes2
Has abstractyes

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