Peripheral Nerve Blocks: Biochemical and Biophysical Mechanisms

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Studies on the mechanism of peripheral nerve block focus on the interaction of local anesthetics with voltage-gated sodium channels.1 Part of a superfamily of tetrameric transmembrane glycoproteins, sodium channels initiate and propagate action potentials in axons, dendrites, and muscle tissue.2-3 Sodium channels exist in three conformations: open, inactivated, and resting. During a neural impulse, the membrane potential becomes less negative as Na+ conductivity increases. At threshold, sodium channels “open” and the membrane potential shoots up.3 After a few milliseconds, sodium channels “inactivate” and the membrane potential returns to baseline.3 Once the membrane repolarizes, sodium channels return to their “resting” conformation.1 As is soon described, sodium channel conformation plays a key role in the functioning of local anesthetics.

As early as 1959, Taylor confirmed that local anesthetics selectively bind and inhibit sodium channels in nerves.4 Subsequent research localized the drug-binding site to the inner pore of the sodium channel, where local anesthetics primarily interact with a phenylalanine in domain IV S6.5 According to Fozzard et al, the affinity of local anesthetics for the binding site depends upon the conformation of the sodium channel. When the sodium channel is in its closed state, the binding affinity is low and Na+ current is only blocked at high concentrations (mM range).5 In contrast, the binding affinity is much higher in the open and open-inactivated states, during which the voltage sensors are deployed outward.5

Strichartz was first to observe the frequency-dependence of local anesthetics.6 According to the model, local anesthetic inhibition of Na+ current increases with repetitive depolarizations.1 Statistically, the percentage of sodium channels in the open and open-inactivated states at any given moment increases as the frequency of action potentials inceases.1 Since the binding affinity is higher for the open state relative to the resting state, a lower concentration of anesthetics is therefore needed at higher frequencies.1

Although the biochemistry at the binding site is well understood, it is not fully understood how local anesthetics block Na+ current at the biophysical level. One possible mechanism is that local anesthetics obstruct the inner pore of sodium channels. Molecular modeling from Hanck et al is consistent with the idea that local anesthetics bind horizontally across the pore.7 According to Sunami et al, the high-affinity binding site is about 10 Å below the selectivity filter, where charged ligands block the channel by occupying sites NaIII or NaIV for permeant ions.2,7 Even if the channel is not completely obstructed, the positive charge placed at the innate sites creates an electrostatic barrier that blocks Na+ influx by Coulombic repulsion.2 Therefore, local anesthetics block Na+ current by a combination of physical and electrostatic obstruction.

An alternative explanation is that local anesthetics interfere with gating. In this model, local anesthetics reduce the movement of charged residues in the voltage sensor, or gating current.5 More specifically, Fozzard et al found that the binding of local anesthetics to phenylalanine locks domain III S4 in its outward position. This prevents the voltage sensor from resetting during repolarization, thereby disrupting the gating mechanism of sodium channels and blocking Na+ current.5

In summary, local anesthetics bind to a phenylalanine in domain IV S6 of sodium channels. The affinity of local anesthetics for this binding site is highest when the sodium channel is in the open state. Once at the binding site, local anesthetics create a physical and electrostatic barrier that blocks Na+ current. In addition, local anesthetics may also interfere with the gating mechanism of sodium channels. Further research is still needed to clarify the biophysical mechanisms by which local anesthetics block Na+ current.

 

References:

1) Becker, Daniel, and Reed, Kenneth. “Local anesthetics: review of pharmacological considerations.” Anesthesia progress vol. 59, 2 (2012): 90-101.

2) “Clinical Pharmacology of Local Anesthetics.” New York School of Regional Anesthesia. 2019.

3) Vadhanan, Prasanna et al. “Physiological and pharmacologic aspects of peripheral nerve blocks.” Journal of anaesthesiology, clinical pharmacology vol. 31, 3 (2015): 384-93.

4) Taylor, RE. “Effect of procaine on electrical properties of squid axon membrane.” Am J Physiol vol. 196 (1959): 1070–1078.

5) Fozzard, Harry et al. “The sodium channel as a target for local anesthetic drugs.” Frontiers in pharmacology vol. 2, 68. 1 Nov. 2011.

6) Strichartz, GR. Local Anesthetics: Handbook of Experimental Pharmacology. Springer-Verlag, 1987.

7) Sunami, A, Dudley, SC, and Fozzard, HA (1997). “Sodium channel selectivity filter regulates antiarrhythmic drug binding.” Proc. Natl. Acad. Sci. U.S.A.

Patient and System Factors Affecting Anesthesiologist First Case Start Performance

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The performance of anesthesiologists, surgical teams, and perioperative systems is commonly measured by the percent of first case on time start (FCOTS) and by first case start delay (FCSD) time (1). First case start delay is one of the factors that contributes to Operating Room (OR) inefficiencies, and can have a high impact on patient satisfaction, particularly for those who are fasting and continuing to wait for surgery (2). Under the Dutch OR Benchmarking initiative, for instance, van Veen-Berkx et al. reported a figure of more than 50,000 minutes lost annually per OR due to surgeries starting late. Similarly, in Germany, more than 70% of general surgery and trauma/orthopedic cases started late in 2011 (2). Metrics such as FCOTS are increasingly being used as measures of individual performance, especially that of anesthesiologists. However, sub-specialization of anesthesiologists across divisions of surgical subspecialties, patient disease severity, and service tracks within a practice group may confound individual measures of FCOTS performance. At the Children’s Hospital and Medical College of Wisconsin, Hoffman et. al conducted a study to examine the effects of patient and system factors on individual-level FCOTS performance measures (1).

To begin, Hoffman et. al extracted anesthesia process and performance data from the perioperative anesthesia data warehouse for all cases from 2013-2018 at the Children’s Hospital of Wisconsin and its surgical center. Primary outcome measures were FCOTS percent and FCSD minutes for individual anesthesiologists, with modifiers of patient age and complexity (according to the ASA physical status classification system), primary surgical service, duration of anesthesia and recovery. Balancing measures of anesthesia procedural intensity, process safety measures, and mortality were also included. Additionally, all data were de-identified prior to export for analysis (1).

After analyzing data from 139,586 cases for 50 anesthesiologists, it was determined that the median individual FCOTS was 63% and the median FCSD was 6.4 minutes (1). There was a strong relationship between delay minutes and FCOTS% (0.2 minutes/percent, r2=-0.70), suggesting a predominance of non-anesthesiologist factors related to delays. The FCSD was strongly related to ASA-PS (2.9 minutes/ASA-PS class, r2=0.16) and anesthesia case time (0.04 minutes/case minutes, R2=0.22). Anesthesiologist exposure to percent of first cases of the day (FCOD) ranged from 12-100%, and median ASA-PS ranged from 1.47 – 3.35. In summary, Hoffman et al. arrived at the conclusion that patient and system factors do indeed contribute strongly to first case on time start performance of anesthesiologists. They also note that exposure to these factors must be accounted for when benchmarking individual performance (1).

With this in mind, there are some ways in which first case start delays and performance can be improved. In 2014, Ramos et al. undertook a study to reduce first case delays at the Hospital das Clinicas of the University of Sao Paulo, the largest public hospital in Latin America (2). They implemented changes focused on increasing care coordination between the OR and the inpatient and ICU units, namely by standardizing patient OR admission using a pre-operative checklist and reducing the uncertainty for post-op ICU availability. These changes resulted in more than 55,000 minutes of OR time saved in one year, which may represent an economy of more than 150,000 USD (2). In the U.S, a Rapid Process Improvement Workshop (RPIW) team at the Dartmouth Hitchcock Medical Center was able to increase their FCOTS % by assessing barriers to prompt first-case starts and redesigning the workflow of patient preparation. One of the changes made, for example, was that OR nurse visits were implemented as the first task, rather than occurring just prior to patient transport. The Dartmouth study improved first-case on-time starts after 16 weeks to 75 percent and the average delay decreased from 7.2 minutes to 4 minutes. All in all, the Dartmouth case study estimated that an improvement to greater than 80 percent on-time starts would result in increased patient and staff satisfaction and nearly $2 million a year in combined cost saving in overtime pay, additional cases and increased revenue, demonstrating the importance of dealing with patient and system factors in first case start delay (3).

References

  1. Hoffmann, G., Scott, J. P., & Berens, R. J. (2019, October 19). Patient and System Factors Affecting Anesthesiologist First Case Start Performance. Retrieved from https://www.abstractsonline.com/pp8/#!/6832/presentation/6140.
  2. P. Ramos, E. Bonfá, P. Goulart, et al. First-case tardiness reduction in a tertiary academic medical center operating room: a lean six sigma perspective. Perioper Care Oper Room Manag, 5 (2016), pp. 7-12
  3.  On-time operating room starts can be improved, increasing patient/staff satisfaction and cost savings. (2013, October 15). Retrieved from https://www.asahq.org/about-asa/newsroom/news-releases/2013/10/on-time-or-starts.

 

An Overview of Peripheral Nerve Blocks

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Peripheral nerve blocks involve the injection of local anesthetic near a nerve – or bundle of nerves – to numb a specific part of the body.1 Commonly used for surgery on the hands, arms, feet, legs, and face, peripheral nerve blocks provide pain relief during and after surgery by blocking the transmission of pain signals from the surgical site.2 Compared to general anesthesia, peripheral nerve blocks offer numerous advantages, including faster recovery time, fewer side effects, no need for an airway device, and reduced postoperative pain.1 Prior to surgery, an anesthesiologist uses ultrasound or electrical stimulation to locate the nerves and determine the optimal injection site.1 The local anesthetic is then injected without irritating the nerves themselves. Depending on the local anesthetic and amount injected, the effects can last a few hours to days.1

Local anesthetics used for peripheral nerve block include lidocaine, ropivacaine, bupivacaine, and mepivacaine.3 These drugs are often combined with additives to reduce onset time and prolong the duration of analgesia.4 Common additives include epinephrine, clonidine, dexmedetomidine, buprenorphine, dexamethasone, tramadol, sodium bicarbonate, and midazolam, with epinephrine being the most popular.4 An α1-adrenoceptor agonist, epinephrine works synergistically with local anesthetics by causing vasoconstriction and decreasing blood flow.4 Mechanistically, epinephrine decreases the diffusion of local anesthetic away from the nerve, which ultimately lengthens the duration of analgesia.4

The mechanism of peripheral nerve blocks is explained in terms of electrophysiology. Local anesthetics act on the voltage-gated sodium channels that initiate and propagate action potentials in neurons.5 Electron microscopic studies reveal that sodium channels are comprised of a bell-shaped transmembrane glycoprotein with four domains and a central pore through which sodium ions flow.5 Previously, it was thought that local anesthetics physically occlude the central pore.6 However, it is now understood that local anesthetics block neurotransmission by binding to specific sites at the pore and creating an electrostatic field that repels positively charged sodium ions.7

After injection at the surgical site, two factors determine the amount of local anesthetic that actually reaches the nerve: the relative mass of the nerve and diffusion across the perineurium. Once injected, the local anesthetic reaches an equilibrium with all tissues, including muscle, bone, connective tissue, etc.5 The mass of the nerve relative to the mass of the surrounding tissue determines the volume of local anesthetic taken up by the nerve.5 Because the mass of the surrounding tissue is typically 5-10 times more than that of the nerve, only a small portion of the injected local anesthetic actually acts at sodium channels.5 In addition to relative mass, diffusion rates affect the amount of local anesthetic that reaches the target site. The perineurium is a sheath of connective tissue that surrounds a bundle of nerve fibers.5 The thicker the perineurium, the lower the rate of diffusion, and the lower the volume of local anesthetic that reaches the site of action at nerves.5

Though generally safe, peripheral nerve blocks occasionally manifest with local anesthetic toxicity in the central nervous system and heart. Causes of local anesthetic toxicity include an allergy, excessive dosage, or intravascular injection.8 Early signs include numbness and tingling in the mouth, metallic taste, and ringing in the ears.8 Complications include seizures, arrhythmias, cardiac arrest, and nerve injuries (the last of which occurs in only 0.029-0.2% of cases).8 Causes of nerve injury include ischemia, compression, direct neurotoxicity, laceration, and inflammation.8 Some evidence suggests that the use of ultrasound lowers the risk of nerve injury to 0.0037%.9

With the widespread acceptance and adoption of ultrasound-guided techniques, peripheral nerve blocks have become much more commonly used by anesthesiologists.5 As researchers continue to develop novel drugs with lower toxicity and longer analgesia, peripheral nerve blocks will become safer and more effective.5

 

References

1) “Regional Anesthesia (Nerve Blocks).” UC San Diego Health. 2019.

2) Healthwise Staff. “Peripheral Nerve Blocks for Anesthesia.” Alberta Health. December 13, 2018.

3) “Common Regional Nerve Blocks (PDF).” UWHC Acute Pain Service. January 2011.

4) Brummett, Chad M, and Brian A Williams. “Additives to local anesthetics for peripheral nerve blockade.” International anesthesiology clinics. Vol. 49, 4 (2011): 104-16.

5) Vadhanan, Prasanna et al. “Physiological and pharmacologic aspects of peripheral nerve blocks.” Journal of anaesthesiology, clinical pharmacology. Vol. 31, 3 (2015): 384-93.

6) McNulty, Megan M et al. “Charge at the lidocaine binding site residue Phe-1759 affects permeation in human cardiac voltage-gated sodium channels.” The Journal of physiology. Vol. 581, Pt 2 (2007): 741-55.

7) GLadsden, Jeff. “Clinical Pharmacology of Local Anesthetics.” New York School of Regional Anesthesia. 2019.

8) El-Boghdadly, Kariem et al. “Local anesthetic systemic toxicity: current perspectives.” Local and regional anesthesia. Vol. 11, 35-44.

9) David Hardman. “Nerve Injury After Peripheral Nerve Block: Best Practices and Medical-Legal Protection Strategies.” Anesthesiology News. July 30, 2015.

Effects of Anesthesia on Phantom Limb Pain

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In 2005, there were 1.6 million people living with limb loss in the US, 60% to 85% of whom suffer from phantom limb pain.1 Phantom limb pain refers to a variety of nociceptive perceptions – ranging from a slight, tingling to a sharp, throbbing pain – perceived in a limb or organ that is physically not present.1 Risk factors associated with phantom limb pain include pain before the amputation, cause of amputation, prosthesis use, and years since amputation.1 Commonly classified as neuropathic, phantom limb pain is presumably related to damage of the central and peripheral neurons.2 As a basic mechanism, the neuromatrix theory proposes that a network of neurons extending into widespread areas of the brain, defined as the neuromatrix, composes the “anatomical substrate of the physical self.”3 Following amputation of an extremity, abnormal impulses can change the neuromatrix pattern, which causes conversion of normal input to pain sensation, i.e. phantom limb pain.3 Although the neuromatrix and other theories provide some insight into the mechanisms of phantom limb pain, a rigorous understanding eludes researchers. Considering that 3.6 million people will live with limb loss in the US by 2050, it is essential to develop therapeutic approaches to attenuate this condition perioperatively.1

Many studies on phantom limb pain focus on methods to prevent postoperative problems via perioperative epidural infusions.4,5 For example, Jahangiri et al found that perioperative epidural infusion of diamorphine, clonidine, and bupivacaine is safe and effective in reducing the incidence of phantom limb pain based on a controlled study of 24 patients undergoing lower limb amputation.5 Of more relevance, there is also a growing literature on the effects of different anesthetic techniques on phantom limb pain.

Ong et al investigated the effects of epidural, spinal, and general anesthesia on pain after lower limb amputation. The study included a cross-sectional survey of 150 patients evaluated 1 to 24 months after their lower limb amputation.6 In the week after surgery, patients receiving epidural anesthesia and patients receiving spinal anesthesia reported significantly less pain than patients receiving general anesthesia.6 After 14 months, there was no difference in stump pain, phantom limb sensation, or phantom limb pain between patients who received epidural anesthesia, those who received spinal anesthesia, and those who received general anesthesia.6 Based on their findings, Ong et al concluded that patients receiving either epidural or spinal anesthesia may experience reduced phantom limb pain in the first week after amputation.6

Ugur et al performed a retrospective study to evaluate the effects of different anesthesia types on phantom limb sensation and phantom limb pain. The researchers mailed a questionnaire to patients who underwent lower extremity amputation between 1996 and 2003 at Erciyes University Hospital.7 In total, 40 patients who received general anesthesia and 27 patients who received spinal anesthesia completed the questionnaire.7 65% of patients in the general anesthesia group and 33% of patients in the spinal anesthesia group experienced phantom limb pain after surgery – representing a statistically significant difference.7 The incidence of phantom limb sensation was 77% for the general anesthesia group and 74% for the spinal anesthesia group, showing no significant difference.7 The researchers concluded that the incidence of phantom limb pain was lower for patients receiving spinal anesthesia.7

The aforementioned studies investigate the effects of general, spinal, and epidural anesthetic techniques on phantom limb pain. However, these studies do not look at the effects of peripheral nerve block. In a more recent study, Sahin et al retrospectively compared the effects of general anesthesia, spinal anesthesia, epidural anesthesia, and peripheral nerve block on postoperative incidence of phantom limb sensation and phantom limb pain.7 The study included 92 patients for 1 to 24 months after surgery, and a standardized questionnaire assessing phantom limb sensation, phantom limb pain, and stump pain postoperatively on a numerical scale of 0 to 10.7 Sahin et al found that patients who received epidural anesthesia and peripheral nerve block perceived significantly less pain in the week after surgery compared to patients who received general anesthesia and spinal anesthesia.7 However, there was no difference in phantom limb pain, phantom limb sensation, or stump pain among the groups after about 14 to 17 months.7

Overall, the literature suggests that some anesthetic techniques – i.e. peripheral nerve blocks and epidural anesthesia – may attenuate phantom limb pain in the first week after amputation, but not in the long run. As researchers continue to elucidate the neurological and physiological mechanisms of phantom limb pain, clinicians may be able to develop improved techniques to reduce symptoms after surgery.

References:

1) Sahin SH, Colak A, Arar C, et al. A retrospective trial comparing the effects of different anesthetic techniques on phantom pain after lower limb amputation. Curr Ther Res Clin Exp. 2011;72(3):127–137.

2) Flor H: Phantom-limb pain: characteristics, causes, and treatment. Lancet Neurol. 2002;1(3):182–9. 10.1016/S1474-4422(02)00074-1.

3) Hill A. Phantom limb pain: a review of the literature on attributes and potential mechanisms. J Pain Symptom Manage. 1999;17:125–142.

4) Nikolajsen L, Ilkjaer S, Christensen JH, et al. Randomised trial of epidural bupivacaine and morphine in prevention of stump and phantom pain in lower-limb amputation. Lancet. 1997;350:1353–1357.

5) Jahangiri M, Jayatunga AP, Bradley JW, Dark CH. Prevention of phantom pain after major lower limb amputation by epidural infusion of diamorphine, clonidine and bupivacaine. Ann R Coll Surg Engl. 1994;76:324 –326.

6) Ong BY, Arneja A, Ong EW. Effects of anesthesia on pain after lower-limb amputation. J Clin Anesth. 2006;18:6000 – 6004.

7) Ugur F, Esmaoglu A, Akin A, et al. Does spinal anesthesia decrease the incidence of phantom pain? Pain Clinic. 2006;18:187–193.

Third-Party Risk Management for Healthcare Companies

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Risk management is an important part of any healthcare company’s business strategy. In addition to preventing financial loss, a good risk management system will also protect patient data. With the growth of cloud services and the increased outsourcing of administrative tasks in the healthcare sphere, companies have shared large amounts of data with a variety of external companies. It is therefore increasingly important for healthcare companies to implement third-party risk management techniques.

Healthcare companies retain large amounts of protected health information (PHI), which is very sensitive and highly susceptible to hacking attempts [1]. In 2018, the healthcare field had the second largest number of data breaches, according to the Identity Theft Resource Center [2]. While a healthcare company may have robust security practices in place, this could be moot if a third-party with access to patient data and poor security practices is breached.

For example, the well-publicized data breaches at Quest Diagnostics and LabCorp were not a result of direct infiltration. Both of these breaches, which exposed the data of 20 million patients, came from an unauthorized user accessing systems owned by American Medical Collection Agency, a third-party bill collection service [3].

Third-party risk management can also be a matter of compliance. The Health Information Technology for Economic and Clinical Health (HITECH) Act expanded HIPAA to include all of a company’s business associates. For many healthcare organizations, this means that they are responsible for the data given to third-parties vendors [4] [5].

A common strategy used by healthcare companies is to switch from a reactive risk management program to a proactive one. Instead of waiting for a breach to develop and implementing new strategies, organizations instead predict where possible breaches may occur and fix them before they develop into problems. However, a majority of respondents in a recent survey on risk management said that they could not keep track of the risks posed by new technologies [6]. For some organizations, integrated risk management (IRM) platforms are a useful solution in identifying and repairing possible weak points.

Companies can also require that their third-party vendors undergo a standardized certification. A common option is the HITRUST CSF certification, which was developed by an alliance of healthcare institutions. HITRUST CSF (Common Security Framework) takes a risk-based approach to HIPAA compliance and has been designed to comply with state requirements, as well. When the University of Pittsburgh Medical Center found itself unable to individually assess the risks presented by its third-party affiliates, it required them to undergo HITRUST CSF certification [6]. As a result, the organization was able to more effectively manage risk without devoting excessive amounts of time to compliance.

On a broader scale, companies can cultivate a culture of transparency internally. Along with a standardized risk management system and third-party compliance checks, a transparent culture encourages accountability across an organization. This culture of transparency also includes systematizing and standardizing risk management processes and sharing them with all applicable parties.

For healthcare companies, third-parties are an integral part of a complete risk management system. By committing to screening third-party vendors, implementing a proactive certification process, and participating in ongoing monitoring, healthcare organizations can insulate themselves from the risks of third-party data breaches.

References:

[1] Keglovits, Dennis. “Healthcare Organizations Need to Do Better with Third-Party Risk Management.” Healthcare Business & Technology, 3 Sept. 2019, www.healthcarebusinesstech.com/healthcare-organizations-need-to-do-better-with-third-party-risk-management/.

[2] Lefkowitz, Josh. “The Growing Challenge of Third-Party Risk and Compliance.” Verdict, 2 Oct. 2019, www.verdict.co.uk/cybersecurity-third-party-risk/.

[3] Friel, Sean. “Third-Party Risk Management: Keeping Your Healthcare Organization’s Information Safe.” Security Magazine, Security Magazine, 24 Sept. 2019, www.securitymagazine.com/articles/90976-third-party-risk-management-keeping-your-healthcare-organizations-information-safe.

[4] Hulme, George V. “Discussing Third-Party Risk Management in the Healthcare Industry.” BitSight, 1 May 2014, www.bitsight.com/blog/discussing-third-party-risk-management-in-the-healthcare-industry.

[5] Mohsin, Tahshina. “Third-Party Risk Management.” Infosec Resources, resources.infosecinstitute.com/category/healthcare-information-security/security-technologies-in-healthcare/third-party-risk-management/.

[6] Barker, Ian. “Managing Third-Party Risk Costs the Healthcare Industry over $23 Billion a Year.” BetaNews, 10 July 2019, betanews.com/2019/07/10/healthcare-third-party-risk/.

[7] Houston, John. “To Ensure Vendor Security: UPMC Turns to the HITRUST CSF Assessment to Help Manage Third-Party Risk.” HITRUST, 2018, provider-tprm.org/public/181109_CaseStudy_UPMC.pdf.