Current Trends in Modalities of Pain Assessment: A Narrative Review

被引:0
|
作者
Chandra, Sarangi S. [1 ]
Pooja, Gupta [1 ]
Kaur, Makkar T. [1 ]
Ramesh, Dodamani [2 ]
机构
[1] All India Inst Med Sci, Dept Pharmacol, New Delhi, India
[2] All India Inst Med Sci, Dept Neurosurg, New Delhi, India
关键词
Multi-dimensional; pain assessment tool; precision pain management; special population; unidimensional; AUTONOMIC NERVOUS-SYSTEM; VISUAL ANALOG SCALE; NUMERICAL RATING-SCALES; LOW-BACK-PAIN; POSTOPERATIVE PAIN; SHORT-FORM; ASSESSMENT TOOLS; CLINICAL-TRIALS; NECK PAIN; SCREENING QUESTIONNAIRE;
D O I
暂无
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Pain is a common complaint among a spectrum of diseases. Although an ideal objective method of pain assessment is lacking, several validated tools are available for use in clinical research and practice. The tool considerations are based upon the parameters to be assessed and factors specific to patient, disease, and availability of instruments. This review classifies and brings the key aspects of currently available pain assessment tools on a single platform to ease the selection process for researchers/practitioners. The tools utilized for pain assessment were collected from articles available in PubMed and Google Scholar databases and classified into the following domains: unidimensional, multi-dimensional, investigation-based, and computerized algorithm-based tools. Their purpose of use and limitations are reviewed. The unidimensional scales are used to describe only the characteristics of pain, like intensity (e.g. numerical rating scale), type (e.g. neuropathic pain questionnaire), or pattern. In contrast, multi-dimensional tools, like Mc Gill Questionnaire, assess not only pain as an individual symptom but also its influence on physical functioning and general well-being. However, certain components like ethnicity, age, cognitive impairment, sedation, and emotion become a limiting factor in selecting the scale. In addition to these scales, a potential role of parameters such as biopotentials/markers has also been shown in pain assessment. Last, artificial intelligence is also being applied in evaluation of pain. Pain measurement is subjective in nature as assessed through questionnaires and observational tools. Currently, multi-dimensional approaches of pain assessment are available, which can lead to precision pain management.
引用
收藏
页码:951 / 966
页数:16
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