Bibliographic record
Abstract
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
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.032 | 0.018 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".