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Evidence-Based Diagnosis: An Introduction to Clinical Epidemiology
Thomas B. Newman, Michael A. Kohn
This is a book about diagnostic testing. It is aimed primarily at clinicians, particularly those
who are academically minded, but it should be helpful and accessible to anyone involved
with selection, development, or marketing of diagnostic, screening, or prognostic tests.
Although we admit to a love of mathematics, we have restrained ourselves and kept the
math to a minimum – a little simple algebra and only three Greek letters, (kappa),
(alpha), and (beta). Nonetheless, quantitative discussions in this book go deeper and are
more rigorous than those typically found in introductory clinical epidemiology or evidencebased
medicine texts.
Our perspective is that of skeptical consumers of tests. We want to make properdiagnoses and not miss treatable diseases. Yet, we are aware that vast resources are spent
on tests that too frequently provide wrong answers or right answers of little value, and that
new tests are being developed, marketed, and sold all the time, sometimes with little or no
demonstrable or projected benefit to patients. This book is intended to provide readers with
the tools they need to evaluate these tests, to decide if and when they are worth doing, and to
interpret the results.
The pedagogical approach comes from years of teaching this material to physicians,mostly fellows and junior faculty in a clinical research training program. We have found
that many doctors, including the two of us, can be impatient when it comes to classroom
learning. We like to be shown that the material is important and that it will help us take
better care of our patients, understand the literature, and/or improve our research. For this
reason, in this book we emphasize real-life examples.
Although this is primarily a book about diagnosis, two of the twelve chapters are about
evaluating treatments – using both randomized trials (Chapter 8) and observational studies
(Chapter 9).
who are academically minded, but it should be helpful and accessible to anyone involved
with selection, development, or marketing of diagnostic, screening, or prognostic tests.
Although we admit to a love of mathematics, we have restrained ourselves and kept the
math to a minimum – a little simple algebra and only three Greek letters, (kappa),
(alpha), and (beta). Nonetheless, quantitative discussions in this book go deeper and are
more rigorous than those typically found in introductory clinical epidemiology or evidencebased
medicine texts.
Our perspective is that of skeptical consumers of tests. We want to make properdiagnoses and not miss treatable diseases. Yet, we are aware that vast resources are spent
on tests that too frequently provide wrong answers or right answers of little value, and that
new tests are being developed, marketed, and sold all the time, sometimes with little or no
demonstrable or projected benefit to patients. This book is intended to provide readers with
the tools they need to evaluate these tests, to decide if and when they are worth doing, and to
interpret the results.
The pedagogical approach comes from years of teaching this material to physicians,mostly fellows and junior faculty in a clinical research training program. We have found
that many doctors, including the two of us, can be impatient when it comes to classroom
learning. We like to be shown that the material is important and that it will help us take
better care of our patients, understand the literature, and/or improve our research. For this
reason, in this book we emphasize real-life examples.
Although this is primarily a book about diagnosis, two of the twelve chapters are about
evaluating treatments – using both randomized trials (Chapter 8) and observational studies
(Chapter 9).
ক্যাটাগোরিগুলো:
সাল:
2020
সংস্করণ:
2nd
প্রকাশক:
Cambridge University Press
ভাষা:
english
পৃষ্ঠা:
383
ISBN 10:
1108500110
ISBN 13:
9781108500111
ফাইল:
PDF, 9.71 MB
IPFS:
,
english, 2020