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(as of Feb 10, 2025 11:54:29 UTC – Details)
“Another winning veterinary memoir deserving of space next to the immortal James Herriot and his heirs”—from the author of All My Patients Kick and Bite (Booklist).
All My Patients Have Tales is a heartwarming and funny collection of stories by a dedicated veterinarian featuring wild horses, porcupine-quill-covered dogs, male cats in labor, an extremely ornery pygmy donkey, an enormous hog, as well as many other domestic, and not so “domestic” animals. Wells begins his work as an inexperienced recent college grad and emerges a caring and beloved veterinarian. Affording the reader an inside glimpse into his daily life, he narrates many uplifting, life-altering, life-threatening, and hilarious episodes.
“A wonderful account of the coming of age of a vet. Jeff Wells has written an honest and poignant account of vet school and his early years in practice.” —Susan Richards, New York Times–bestselling author of Chosen by a Horse
“What a treat it is to read tales from the tail-bearers. In this most welcome book we not only learn about animals in need, but also what it is like to be a veterinarian with a heart.” —Marc Bekoff, author of The Emotional Lives of Animals
“Anyone who has a pet will absolutely love this charming and humorous collection of personal experiences with animals.” —John A. Hoyt, President Emeritus, The Human Society of the United States
“A humorous and insightful look at his life and work with a wide range of animals.” —Publishers Weekly
ASIN : B002LA0AK2
Publisher : St. Martin’s Press; Illustrated edition (July 2, 2024)
Publication date : July 2, 2024
Language : English
File size : 2942 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Enabled
Print length : 234 pages
Customers say
Customers find the book easy to read and engaging. They appreciate the well-written descriptions and humorous stories about animals. The book is described as heartwarming, insightful, and soulful for readers.
AI-generated from the text of customer reviews
