Use of herbal medication in the perioperative period: Potential adverse drug interactions

Use of herbal medications and supplements has experienced immense growth over the last two decades, with retail sales in the USA exceeding $13 billion in 2021. Since the Dietary Supplement Health and Education Act (DSHEA) of 1994 reduced FDA oversight, these products have become less regulated. Data from 2012 shows 18% of U.S. adults used non-vitamin, non-mineral natural products. Prevalence varies regionally, with higher use in Western states. Among preoperative patients, the most commonly used herbal medications included garlic, ginseng, ginkgo, St. John's wort, and echinacea. However, 50-70% of surgical patients fail to disclose their use of herbal medications to their physicians, and most fail to discontinue them preoperatively. Since herbal medications can interact with anesthetic medications administered during surgery, the American Society of Anesthesiologists (ASA) and the American Association of Nurse Anesthetists (AANA) recommend stopping herbal medications 1-2 weeks before elective surgical procedures. Potential adverse drug effects related to preoperative use of herbal medications involve the coagulation system (e.g., increasing the risk of perioperative bleeding), the cardiovascular system (e.g., arrhythmias, hypotension, hypertension), the central nervous system (e.g., sedation, confusion, seizures), pulmonary (e.g., coughing, bronchospasm), renal (e.g., diuresis) and endocrine-metabolic (e.g., hepatic dysfunction, altered metabolism of anesthetic drugs). During the preoperative evaluation, anesthesiologists should inquire about the use of herbal medications to anticipate potential adverse drug interactions during the perioperative period.

Use of electroanalgesia and laser therapies as alternatives to opioids for acute and chronic pain management

The use of opioid analgesics for postoperative pain management has contributed to the global opioid epidemic. It was recently reported that prescription opioid analgesic use often continued after major joint replacement surgery even though patients were no longer experiencing joint pain. The use of epidural local analgesia for perioperative pain management was not found to be protective against persistent opioid use in a large cohort of opioid-naïve patients undergoing abdominal surgery. In a retrospective study involving over 390,000 outpatients more than 66 years of age who underwent minor ambulatory surgery procedures, patients receiving a prescription opioid analgesic within 7 days of discharge were 44% more likely to continue using opioids 1 year after surgery. In a review of 11 million patients undergoing elective surgery from 2002 to 2011, both opioid overdoses and opioid dependence were found to be increasing over time. Opioid-dependent surgical patients were more likely to experience postoperative pulmonary complications, require longer hospital stays, and increase costs to the health-care system. The Centers for Disease Control and Prevention emphasized the importance of finding alternatives to opioid medication for treating pain. In the new clinical practice guidelines for back pain, the authors endorsed the use of non-pharmacologic therapies. However, one of the more widely used non-pharmacologic treatments for chronic pain (namely radiofrequency ablation therapy) was recently reported to have no clinical benefit. Therefore, this clinical commentary will review evidence in the peer-reviewed literature supporting the use of electroanalgesia and laser therapies for treating acute pain, cervical (neck) pain, low back pain, persistent post-surgical pain after spine surgery (“failed back syndrome”), major joint replacements, and abdominal surgery as well as other common chronic pain syndromes (for example, myofascial pain, peripheral neuropathic pain, fibromyalgia, degenerative joint disease/osteoarthritis, and migraine headaches).

A novel visual facial anxiety scale for assessing preoperative anxiety

Background

There is currently no widely accepted instrument for measuring preoperative anxiety. The objective of this study was to develop a simple visual facial anxiety scale (VFAS) for assessing acute preoperative anxiety.

Methods

The initial VFAS was comprised of 11 similarly styled stick-figure reflecting different types of facial expressions (Fig 1). After obtaining IRB approval, a total of 265 participant-healthcare providers (e.g., anesthesiologists, anesthesiology residents, and perioperative nurses) were recruited to participate in this study. The participants were asked to: (1) rank the 11 faces from 0–10 (0 = no anxiety, while 10 = highest anxiety) and then to (2) match one of the 11 facial expression with a numeric verbal rating scale (NVRS) (0 = no anxiety and 10 = highest level of anxiety) and a specific categorical level of anxiety, namely no anxiety, mild, mild-moderate, moderate, moderate-high or highest anxiety. Based on these data, the Spearman correlation and frequencies of the 11 faces in relation to the 11-point numerical anxiety scale and 6 categorical anxiety levels were calculated. The highest frequency of a face assigned to a level of the numerical anxiety scale resulted in a finalized order of faces corresponding to the 11-point numeric rating scale.

Results

The highest frequency for each of the NVRS anxiety scores were as follow: A0, A1, A2, A3, A4, A5, A7, A6, A8, A9 and A10 (Fig 2). For the six categorical anxiety levels, a total of 260 (98.1%) participants chose the face A0 as representing ‘no’ anxiety, 250 (94.3%) participants chose the face A10 as representing ‘highest’ anxiety and 147 (55.5%) participants chose the face A8 as representing ‘moderate-high’ anxiety. Spearman analysis showed a significant correlation between the faces A3 and A5 assigned to the mild-moderate anxiety category (r = 0.58), but A5 was ultimately chosen due to its higher frequency compared to the frequency of A3 (30.6% vs 24.9%)(Fig 3). Similarly, the correlation of the faces A7 and A6 was significantly correlated with moderate anxiety (r = 0.87), but A7 remained because of its higher frequency (35.9% vs 22.6%). Using frequency and Spearman correlations, the final order of the faces assigned to the categories none, mild, mild-moderate, moderate, moderate-high and highest anxiety levels was A0, A1, A5, A7, A8 and A10, respectively (Fig 4).

Conclusion

The proposed VFAS was a valid tool for assessing the severity of acute [state] anxiety, and could be easy to administer in routine clinical practice.