کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
5565266 1563218 2017 5 صفحه PDF سفارش دهید دانلود کنید
عنوان انگلیسی مقاله ISI
Generalisability of prognostic factor research: further analysis of data from the IIPCOS2 study
ترجمه فارسی عنوان
عمومی بودن تحقیقات فاکتورهای پیش آگهی: تجزیه و تحلیل بیشتر داده ها از مطالعه IIPCOS2
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کلمات کلیدی
عوامل پیش آگهی؛ قضیه بیز؛ نسبت احتمالی؛ احتمال شرطی؛ ارزیابی محدود شرایط؛ IIPCOS2؛ سرفه؛ بلادونا؛
موضوعات مرتبط
علوم پزشکی و سلامت پزشکی و دندانپزشکی طب مکمل و جایگزین
چکیده انگلیسی


- Prognostic factor research in homeopathy can be done by applying Bayes' theorem.
- Variants of Bayes' theorem are Likelihood Ratio and conditional probability.
- Research in subpopulations of a condition can be done wherein it would be better to use conditional probability.
- Utility and limitations of condition confined assessment in prognostic factor research.
- Research protocols can be designed for applying prognostic factor research in a universal manner.

Prognostic factor research is important as it helps in refining diagnosis, taking clinical and therapeutic decisions, enhances the design and analysis of intervention trials and helps to identify targets for new interventions that aim to modify the course of a disease. Prognostic factor research in homeopathy can be done by applying Bayes' theorem. This paper considers Bayes' theorem; Likelihood Ratio, conditional probability and research in subpopulations of a condition with examples. We analysed the likelihood ratios for 11 homeopathic medicines for the symptom 'cough' and other upper respiratory tract symptoms, based on data from the IIPCOS2 study. This yielded useful information since several medicines, including Belladonna, had LR >1 for cough, indicating that cough is not an indication for this medicine. The implications for improving homeopathic prescribing are discussed.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Homeopathy - Volume 106, Issue 3, August 2017, Pages 155-159
نویسندگان
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