ISSN NUMBER: 1938-7172
Issue 6.8

Michael A. Fiedler, PhD, CRNA

Contributing Editors:
Penelope S Benedik, PhD, CRNA, RRT
Mary A Golinski, PhD, CRNA
Gerard Hogan Jr., DNSc, CRNA
Alfred E Lupien, PhD, CRNA, FAAN
Lisa Osborne, PhD, CRNA
Dennis Spence, PhD, CRNA
Cassy Taylor, DNP, DMP, CRNA
Steven R Wooden, DNP, CRNA

Assistant Editor
Jessica Floyd, BS

A Publication of Lifelong Learning, LLC © Copyright 2012

New health information becomes available constantly. While we strive to provide accurate information, factual and typographical errors may occur. The authors, editors, publisher, and Lifelong Learning, LLC is/are not responsible for any errors or omissions in the information presented. We endeavor to provide accurate information helpful in your clinical practice. Remember, though, that there is a lot of information out there and we are only presenting some of it here. Also, the comments of contributors represent their personal views, colored by their knowledge, understanding, experience, and judgment which may differ from yours. Their comments are written without knowing details of the clinical situation in which you may apply the information. In the end, your clinical decisions should be based upon your best judgment for each specific patient situation. We do not accept responsibility for clinical decisions or outcomes.

Table of Contents

Is alcohol-based hand disinfection equivalent to surgical scrub before placing a central venous catheter?

What factors affect intrapartum maternal temperature? A prospective cohort study: maternal intrapartum temperature

Operating room team members’ views of workload, case difficulty, and nonroutine events

Who is at risk for postdischarge nausea and vomiting after ambulatory surgery?

The limits of succinylcholine for critically ill patients

Does intraoperative ketamine attenuate inflammatory reactivity following surgery? A systematic review and meta-analysis



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Is alcohol-based hand disinfection equivalent to surgical scrub before placing a central venous catheter?

Anesth Analg. 2012;114:622-5

Burch TM, Stanger B, Mizuguchi KA, Zurakowski D, Reid SD


Purpose The purpose of this study was to compare the effectiveness of alcohol-only hand cleaner, waterless surgical scrub with Avagard ™, and a traditional surgical scrub prior to central line placement.


Background Alcohol-only hand cleaner has been shown to reduce the spread of infection in health care settings. In school children, alcohol-only hand cleaner has been shown to prevent the spread of illness as well as washing with soap. A waterless “surgical scrub” with 1% chlorhexidine gluconate and 61% ethyl alcohol (trade name Avagard) has been shown to sanitize hands as well as a traditional surgical scrub. The Avagard waterless surgical scrub requires only 3 minutes to perform compared to a 5 minute traditional surgical scrub. Cleaning one’s hands by a method other than a traditional surgical scrub can be performed faster. And, since alternate cleaning methods do not require a scrub sink, hand cleaning can be performed almost anywhere, for example, in the OR after having performed induction of general anesthesia.


Methodology Five different methods of hand cleaning were used in this study.

  1. traditional surgical scrub, 5 minutes with water, brush, 4% chlorhexidine soap
  2. traditional surgical scrub, 15 minute break, then use of alcohol-only hand sanitizer
  3. alcohol-only hand sanitizer (62% ethyl alcohol)
  4. alcohol-only hand sanitizer, 15 minute break, then traditional surgical scrub
  5. waterless surgical scrub (1% chlorhexidine gluconate & 61% ethyl alcohol; Avagard) only

All participants were residents, fellows, or attending anesthesiologists experienced with surgical hand scrub technique. No patients were involved. Providers with abrasions, skin lesions, or artificial nails were excluded from the study. The study was performed in an empty OR before the start of morning cases. Participants who had a 15 minute break prior to hand sanitizer (methods #2 & #4) performed their normal duties during that time, such as setting up for their first anesthetic. They had no patient contact during their break. Fingers were cultured on a blood agar plate after scrubbing and drying with a sterile towel. The cultures were grown for 24 hours at 37°C. All other hand cleaning methods were compared to a traditional surgical scrub, which was defined as the “gold standard.”


This study was limited to examining the pathogens on a provider’s hands after various methods of hand cleaning. It did not examine the rates of central line infections following insertion by hands cleaned with different methods.


Result Cultures were described as the number of agar plates that grew organisms. Growth was seen significantly more often after cleaning hands only with alcohol-only disinfectant (see figure 1). Of the five methods tested, cleaning the hands with hand sanitizer was the only method that was statistically significantly different than a traditional surgical scrub (P=0.001). Each of the other methods was statistically no different than a traditional surgical scrub (P values between 0.49 and 0.99). Perhaps most clinically important, the Avagard waterless surgical scrub with 1% chlorhexidine and 61% alcohol, which can be performed in the OR in about 3 minutes, was equally effective as a traditional surgical scrub at the sink.



Figure 1. Percent of Agar Plates with Growth

Figure 1

Notes: Method 1 = traditional surgical scrub, 5 minutes with water, brush, 4% chlorhexidine soap. Method 2 = traditional surgical scrub, 15 minute break, then use of alcohol-only hand sanitizer. Method 3 = alcohol-only hand sanitizer (62% ethyl alcohol). Method 4 = alcohol-only hand sanitizer, 15 minute break, then traditional surgical scrub. Method 5 = waterless surgical scrub (1% chlorhexidine gluconate & 61% ethyl alcohol; Avagard) only. Data from Anesth Analg. 2012;114:622-5.



Conclusion Alcohol only hand cleanser (method 3) was significantly less effective than a traditional surgical scrub. It is not recommended as the sole method for hand cleansing prior to placing central lines. Properly applied, Avagard waterless surgical scrub (method 5) was equally effective compared to the traditional surgical scrub (method 1).



More and more research evidence is showing us that our hands are rarely as clean as we think, they become contaminated with pathogens quickly, and that the hands of anesthesia providers play a significant role in spreading these pathogens to patients. Often times, the pathogens move from the patient, to our hands, then back to the IV set where they gain entry into the circulation. They often move from one patient to the next via contaminated anesthesia equipment; often the pop off valve or flowmeter knobs, which may not always be cleaned thoroughly between cases. Perhaps worst of all, since infections usually take days or weeks to show up, we rarely know that we’ve had a part in the patient developing an infection. (And, clearly, many other healthcare providers play a role in this process as well.) But, in the end, post surgical infections add up to one of the most frequent and costly complications in all of healthcare.(1)


We’ve long known that frequent hand washing is a key to preventing the spread of infection. This study helps us in two ways. First, while alcohol based hand sanitizer is useful, this study shows us that it has limitations. We mustn't put too much faith in hand sanitizer. Second, there is something that comes in a bottle and doesn’t require a scrub sink that, used according to instructions, will clean our hands just as well as a traditional surgical scrub.


The problem of infection control in anesthesia grows larger the more we learn. We’re going to have to assess and improve many of our current practices and procedures, and those of support personnel, if we are to reduce the role anesthesia providers play in infecting patients. But one thing is clear, keeping our hands as clean and pathogen free as possible is crucial to the process. From this study we learn more about effective ways to do that.

Michael A. Fiedler, PhD, CRNA

1. Van Den Bos J, Rustagi K, Gray T, Halford M, Ziemkiewicz E, Shreve J. The $17.1 Billion Problem: The Annual Cost Of Measurable Medical Errors. Health Aff. 2011;30:596-603

For more information on this topic see the following in previous issues of Anesthesia Abstracs.



© Copyright 2012 Anesthesia Abstracts · Volume 6 Number 8, August 31, 2012

Obstetric Anesthesia
What factors affect intrapartum maternal temperature? A prospective cohort study: maternal intrapartum temperature

Anesthesiology 2012;117:302-8

Frölich MA, Esame A, Zhang K, Wu J, Owen J


Purpose The purpose of this study was to identify factors associated with noninfectious maternal temperature elevation during active labor.


Background Maternal infections are the most common cause of intrapartum temperature elevation. Recent research has suggested an association between epidural analgesia and temperature elevation during active labor. Additionally, some reports suggest intrapartum temperature elevation may be associated with poor neonatal outcomes. There are conflicting results in the literature; some suggesting epidural analgesia may be the cause of maternal fever, while others have not reported this finding.


The theories suggested explaining the association between maternal fever and epidural analgesia are based on the concept that epidural analgesia may suppress heat-dissipating mechanisms such as pain-associated hyperventilation, or that epidural analgesia may promote placental inflammatory processes which in turn trigger maternal fever. However, sympathetic blockade from epidural analgesia should result in hypothermia secondary to redistribution of heat from the core to the periphery. Furthermore, other factors besides epidural use may influence temperature changes during labor. For example, prolonged labor in patients receiving oxytocin who have a long time from rupture of membranes to delivery may result in an inflammatory process. This could explain the temperature elevation seen in some parturients.


This study sought to evaluate the time course of maternal temperature changes and examine whether or not duration of labor, epidural analgesia, oxytocin dose, body mass index (BMI), or length of time from rupture of membranes where associated with maternal temperature elevation.


Methodology This was a prospective cohort study of 81 women scheduled for induction of labor. Patients were excluded if they had conditions that would affect normal temperature regulation, such as chorioamnionitis, or received medications such as acetaminophen, prostaglandins, or ibuprofen; had active cardiac disease, pulmonary disease, or neurologic disease. Epidural analgesia consisted of bupivacaine 0.1% with 2 µg/mL fentanyl administered via patient controlled epidural analgesia using a basal rate of 8 mL/hr and a demand bolus of 4 mL every 20 minutes. Oxytocin was titrated by nurses based on a standard protocol. After rupture of membranes, an intrauterine pressure catheter was placed in all patients. Temperature was measured orally every hour. Statistical analysis and sample size calculation were appropriate.


Result A total of 81 patients completed the study. Average labor duration was 14 ± 7 hours, length of rupture of membranes was 8 ± 5.6 hours, and BMI was 34.6 ± 9 kg/m2. Median duration of labor was 8 hours. The majority of patients were white (47%) and then African American (40%). Approximately 56% of patients were GBS positive (Group B Streptococcus). The most common parity (number of vaginal births) was 0 (40%) and next most common was 1 (31%).


A mixed linear regression model was used to estimate the temperature slope, or change in temperature per hour. The temperature increased 0.017° C per hour which indicated the temperature increased significantly over time (P = 0.009). Fifty-four percent (54%) of patients had a positive temperature slope (increasing temperature over time) and 46% had a negative temperature slope. Patients with increased BMI had a larger increase in temperature over time (P = 0.0008). Similarly, in patients whose temperatures increased, time from rupture of membranes was associated with a much larger temperature change over time (slope). Total oxytocin dose was not associated with temperature change over time.


In patients who received epidural analgesia, temperature slopes were compared for the four hours before and after epidural initiation. No significant difference was found in the temperature slope before or after initiation of epidural analgesia. Epidural analgesia had no effect on the change in temperature over time.


Conclusion In this study, induced labor was associated with a small temperature increase over time. Patients with a higher BMI and longer duration from rupture of membranes to delivery were more likely to experience temperature elevations during labor. Epidural analgesia had no effect on maternal temperature.



I thought this was a well done cohort study. Temperature studies are difficult to conduct, and the investigators did a good job of controlling for many of the factors that may confound their results (i.e., excluded patients with chorioamnionitis or those who received prostaglandins or acetaminophen; measured temperature orally). Therefore, this study provides some reassuring evidence to anesthesia providers that epidural analgesia use is NOT associated with increasing temperature during labor.


It is probably not surprising that prolonged rupture of membranes was associated with a more pronounced temperature elevation. Prolonged rupture of membranes may trigger an inflammatory response or subclinical infection that probably contributes to the temperature elevation seen. The finding of an association between increasing BMI and temperature elevation is interesting, and it may be that obesity as well contributes to an inflammatory response and secondary temperature elevation, as previous research on obesity has found a link between obesity and inflammation.


One limitation of this study was that the investigators did not report the total amount of local anesthetic administered, or whether or not patients required additional top-up boluses of stronger concentrations of local anesthesia for labor analgesia. This could have potentially influenced the results. I also would have liked to have known about the neonatal outcomes. However, this would have required a much larger sample size. Nonetheless, I still think this was a good study that provides us some evidence demonstrating epidural analgesia has no effect on maternal temperature.

Dennis Spence, PhD, CRNA

The views expressed in this article are those of the author and do not reflect official policy or position of the Department of the Navy, the Department of Defense, the Uniformed Services University of the Health Sciences, or the United States Government.

© Copyright 2012 Anesthesia Abstracts · Volume 6 Number 8, August 31, 2012

Patient Safety
Operating room team members’ views of workload, case difficulty, and nonroutine events

J Healthc Quality 2012:34:16-24

Minnic AF, Donagheny B, Stagle J, Weinger MB


Purpose The purposes of this study were to describe operating room providers’ perceptions of workload, case difficulty and individual provider factors as they relate to patient safety.


Background Safety studies often collect data on errors, adverse events, or critical incidents that cause patient harm. Information from near misses (called nonrountine events in this study) can contribute to a fuller understanding of patient safety. In a near miss, no actual harm occurs to the patient, even though the care delivery falls below standard. Near misses could result from excessive workload, case difficulty and/or factors intrinsic to the individual provider or environment.


Methodology Data for this study were collected through interviews and focus groups at 3 Veterans’ Administration hospitals. A total of 38 surgical nurses, 12 surgeons and 18 anesthesia providers (about half anesthesiologists and half nurse anesthetists) participated in the interviews.


Result Team members agreed that workload was more than simply the number of cases performed. Anesthesia and surgeons included teaching and administration as part of workload. Nurses and anesthesia felt that workload increased as a result of changes in schedule and poor surgeon communication. Case difficulty was viewed as adding to workload only if the difficulty was unexpected. The relationship of workload and case difficulty was described by one anesthesia provider as a result of “how sick the patient, how good the surgeon.”


All team members felt near misses were caused by external events; as opposed to factors related to the individual provider. Another source perceived to increase the number of near misses was when a number of unfavorable factors occurred one after another; termed a cascade effect. Anesthesia and nurses were more concerned about external events and the cascade effect than surgeons. Nurses also identified OR noise as a cause of near misses.

Of the many specific unfavorable factors identified by team members, eight were believed to be frequent contributors to the cascade effect:

  • Surgeon who has never met the patient.
  • Equipment/supplies missing or not functioning.
  • Surgeon alters surgical plan the day of surgery.
  • Providers unfamiliar with the procedure.
  • Unscheduled case late in the day or after day shift.
  • Providers feel surgeon does not listen or creates atmosphere of communication fear.
  • Equipment, supplies, or blood not available at beginning of procedure.
  • Patient’s anatomy or physiologic responses are atypical.


Conclusion While OR team members agreed about many things, their perceptions about workload and case difficulty did vary. Perspectives from all professions are needed to get a full picture of the OR safety environment.


Identification of the cascade effect is consistent with a prevailing safety axiom that adverse outcomes are rarely the result of a single isolated error. Near misses resulting from external factors or noise are less appreciated areas of patient safety. New strategies will be needed to gather more information about external factors and noise, since this is not part of routine chart documentation. This study identified potential causes of near misses, which can contribute to developing processes that improve patient safety.



Despite tremendous improvements in anesthesia specifically and health care in general, adverse events remain more common that anyone would like. The number of safety policies and checklists that anesthesia providers must manage seems to grow at an exponential rate. No wonder some of us get irritated by all of it. And yet, we are patient advocates and patient safety always comes first. None of us are irritated by anything that will truly protect patients. It is policy that we perceive as ungrounded and useless that is the source of our irritation.


Safety policies can, and should, be evidence based. This study is an example of how evidence based safety policies can be developed. The authors asked the folks in the trenches about their workload and case difficulty. Any guidelines and recommendations that may be derived from this study will be evidence based and grounded in actual practice that can make a true difference in patient outcomes.


Additionally, many of us feel that the near misses go mostly unreported. This study gathered data directly from the team members who witnessed the near misses that currently escape our documentation efforts. This study gives us a list of 8 red flags that might be associated with near misses. Clinicians could form their own inner checklist of these factors, with the recognition that more than one factor calls for above standard vigilance. When cases are added on to the schedule late in the day, it wouldn’t hurt to be sure the anesthesia provider is very familiar with the procedure. The best time to be providing anesthesia for procedures you have limited experience with, is earlier in the day. If a surgeon makes a last minute change in plan, that should trigger all team members to make another check of all needed equipment and supplies. There are many other examples of how we could respond to the cascade of factors that are most likely to cause potential danger for our patients. Patient safety is always our first priority and nurse anesthetists provide excellent patient safety. This study provides us additional information to make our care even better.

Cassy Taylor, DNP, DMP, CRNA

© Copyright 2012 Anesthesia Abstracts · Volume 6 Number 8, August 31, 2012

Who is at risk for postdischarge nausea and vomiting after ambulatory surgery?

Anesthesiology 2012;117:475-86

Apfel CC, Phillip BK, Cakmakkaya OS, Shilling A, Shi YY, Leslie JB, Allard M, Turan A, Windle P, Odem-Forren J, Hooper VD, Radke OC, Ruiz J, Kovac A


Purpose The purpose of this study was to identify risk factors and develop a risk score for postDischarge nausea and vomiting (PDNV) after ambulatory surgery.


Background Approximately 25% of all surgical patients will develop postoperative nausea and vomiting (PONV). While there are published consensus guidelines to help identify and treat patients at risk for PONV, further research is needed to identify risk factors for the development of postDischarge nausea and vomiting. This is especially important given that more than 60% of surgeries in the United States are now performed on an ambulatory basis. Having a simplified risk score would help anesthesia providers tailor prophylactic regimens to prevent PDNV in at-risk patients.


In this study the investigators examined the incidence of PONV and PDNV. They also identified risk factors and a risk score for the development of PDNV in a group of ambulatory surgery patients. PONV was defined to include the time period from PACU admission until discharge home. PDNV was defined to include the time period from discharge home until 48 hours after emergence from anesthesia.


Methodology This was a multicenter study conducted on 2,493 adults at 12 ambulatory surgery centers in academic centers around the United States. All patients were scheduled for outpatient surgery in which general anesthesia with intubation or laryngeal mask airway placement was anticipated. Anesthetic agents/techniques and PONV antiemetic prophylactic regimens used were based on local institution standards. Nausea and/or vomiting were evaluated in the PACU at 30, 60 and 120 min after surgery using an 11-point verbal numeric rating scale. Severe nausea was defined as a score of 7 or greater on the scale, and severe vomiting as three or more emetic episodes during any given time interval. Patients were provided with a diary and they recorded the severity and incidence of nausea and/or vomiting after discharge home for 48 hours after emergence from anesthesia.


The primary outcome was the percentage of patients with PDNV until 48 hours after emergence from anesthesia. Secondary outcomes included:

  1. percentage of patients with vomiting after discharge
  2. percentage of patients with nausea after discharge
  3. percentage of patients with PONV in PACU
  4. PONV and PDNV severity incidence

Multiple logistic regression was used to identify risk factors and develop a risk score for postDischarge. Sample size calculation was appropriate.


Result A total of 2,170 patients were included in the analysis. The average age of patients was 50 yrs. A majority of patients were nonsmoking (85%), Caucasian (74%), female (65%) with 30% having a history of PONV.

The four most common surgical procedure types included:

  1. general surgery (20%) (41% of general surgery = laparoscopic cholecystectomy)
  2. gynecological surgery (11%)
  3. arthroscopic knee surgery (11%)
  4. breast surgery (10%)

Laparoscopic approaches were used in 38% of all surgeries. A majority of patients (66%) received sevoflurane. A prophylactic serotonin receptor antagonist antiemetic was administered to 77% of patients, 48% received dexamethasone, 13% a dopamine antagonist, and 2.5% a histamine antagonist. Total intravenous anesthesia was not used, although 752 patients (35%) received additional boluses or infusions of propofol. There were 35% who received two intraoperative antiemetics and 12% who received three intraoperative antiemetics.


The overall incidence of postDischarge nausea and vomiting was 37%. The overall incidence of PONV was 21%. (See Figure 1). During both time periods the following factors were independent predictors of PONV and PDNV (Table 1):

  1. female gender
  2. age < 50
  3. history of PONV
  4. opioid use in the PACU

Additional predictors that increased the risk of PONV included >125 mcg of fentanyl intraoperatively, and arthroscopic and laparoscopic surgical approaches. Ondansetron administration intraoperatively decreased PONV incidence.


The only additional predictor of PDNV was nausea in the PACU. Patients who experienced nausea in the PACU had a 3-fold increased risk for PDNV.


Risk factors that were not independent predictors of PONV or PDNV included a history of motion sickness or migraines, ASA physical status, drinking status, and adjuvant peripheral nerve blocks.


A simplified risk score for PDNV in ambulatory surgery patients demonstrated that when zero, one, two, three, four, and five risk factors were present the incidence of PDNV was 11%, 18%, 31%, 49%, 59%, and 80% respectively.



Figure 1. Incidence of PONV and PDNV.

Figure 1

Note: The incidence of severe vomiting was 0.2% in the PACU.



Table 1. Independent Predictors of PONV and PDNV

PONV Period

Adjusted OR

PDNV Period

Adjusted OR

Patient Factors

Female gender


Female gender


Age <50 yrs


Age < 50 yrs






Intraoperative Variables

>125 µg fentanyl in surgery








Surgical Approach










Opioids in PACU


Opioids in PACU




Nausea in PACU


Note: OR = odds ratio


Conclusion Almost 40% of patients experienced PDNV. Anesthesia providers can use the simplified risk score developed in this study to identify patients who may be at risk for PDNV and thus benefit from prophylactic long-acting antiemetics.



PDNV is not a new problem, however it is a less well understood phenomenon compared to PONV. In this study, 37% of patients experienced PDNV, with over 13% experiencing severe nausea. These results tell me that we need to do a better job of identifying and prophylactically treating patients with long-acting antiemetics (e.g., aprepitant, scopolamine) using evidence-based guidelines.


The use of simplified risk scores, where each risk factor is given one point, make it easy for anesthesia providers to quantify a given patients’ risk of PONV or PDNV. However, these risk scores do not tell us which factors are most significant. For example, the strongest risk factor for PONV was a laparoscopic procedure (i.e., cholecystectomy). These patients had a 2.4-fold increased risk of PONV. For PDNV, nausea in the PACU was the strongest predictor, which increased the risk 3-fold. I think anesthesia providers should keep these factors in mind when deciding which patients should receive prophylaxis.


It is not surprising that ondansetron and dexamethasone did not reduce the incidence of PDNV up to 48 hours after emergence from anesthesia. These medications have a relatively short half-life when compared to long acting agents such as aprepitant or scopolamine. I think this brings home the point that we should start thinking more about utilizing some of these long acting antiemetic agents in high-risk patients. Anesthesia providers should use the risk factors and risk scoring system to help in the prevention of PDNV.

Dennis Spence, PhD, CRNA

The views expressed in this article are those of the author and do not reflect official policy or position of the Department of the Navy, the Department of Defense, the Uniformed Services University of the Health Sciences, or the United States Government.

© Copyright 2012 Anesthesia Abstracts · Volume 6 Number 8, August 31, 2012

The limits of succinylcholine for critically ill patients

Anesth Analg. 2012;115:873-9

Blanié A, Ract C, Leblanc PE, Cheisson G, Huet O, Laplace C, Lopes T, Pottecher J, Duranteau J, Vigué B


Purpose The purpose of this study was to identify factors associated with increases in arterial potassium concentrations after succinylcholine administration in ICU patients. A secondary purpose was to analyze the incidence of hyperkalemia ≥ 6.5 mmol/L under these same conditions.


Background Succinylcholine is often used to facilitate endotracheal intubation in high acuity patients. It causes paralysis by occupying nicotinic receptors and causing skeletal muscle cell depolarization. Part of the mechanism of skeletal muscle depolarization involves the movement of potassium from the intracellular to the extracellular space. As a result, when succinylcholine is used to cause skeletal muscle paralysis, plasma potassium levels rise temporarily; generally no more than of 0.5 to 1 mmol/L. Under some circumstances, however, the increase in plasma potassium may be much greater, resulting in acute, life threatening, hyperkalemia. Either way, peak plasma concentrations of potassium occur about 4 minutes after succinylcholine administration.


One of the most important causes of hyperkalemia after succinylcholine administration is a prior upregulation of nicotinic receptors. Risk factors for this upregulation are known and include:

  • anatomic denervation of skeletal muscle (e.g. paraplegia or quadriplegia > 48 hours old)
  • prolonged administration of a neuromuscular blocking drug
  • major burns
  • prolonged immobilization.

Despite what is known about hyperkalemia following succinylcholine administration, the contraindications to succinylcholine use in the ICU are not agreed upon. Previously, one small study found a correlation between the length of time a patient had been in the ICU and the magnitude of the increase in serum potassium after succinylcholine administration.


Methodology This was a prospective, observational study of established patterns of care over 18 months in a 22 bed trauma center surgical ICU. The study included all emergency intubations with succinylcholine in ICU patients. The choice of muscle relaxant and whether or not an induction drug was used was made by the attending physician. Patients with a severed spinal cord >48 hours old, burns, or a baseline potassium > 5.5 mmol/L were not included in the study. Also excluded were those patients who did not have a recent pre-intubation potassium or had their post intubation potassium drawn more than 5 minutes after succinylcholine administration. The normal post intubation arterial blood gas was collected between 3 and 5 minutes after succinylcholine administration to insure measurement of the peak potassium concentration. Statistical analysis was well thought out and rigorous.


Result Data from131 patients and 153 intubations were analyzed. Exclusion criteria were applied to 65 other intubations. Median patient age was 62 years and 72% were male. The median dose of succinylcholine was 1 mg/kg. Etomidate was used for induction in 88% of intubations. All patients received an induction drug. The median pre-succinylcholine potassium was 4.0 mmol/L. The median increase in potassium was 0.4 mmol/L.


Factors associated with an increase in potassium after succinylcholine administration to ICU patients included:

  • length of ICU stay (P<0.001)
  • acute cerebral pathology (P=0.005)
  • previous use of succinylcholine (P<0.001)
  • motor deficit > 48 hours (P=0.001)

When a multivariate analysis was performed the only risk factor that remained significant was the length of ICU stay prior to intubation (𝝆=0.56, P<0.001). The change in serum potassium after succinylcholine administration increased linearly with the length of the patients’ stay in the ICU.


In 11 cases (7% of intubations) the potassium after succinylcholine administration was ≥6.5 mmol/L. In 2 of these, ventricular tachycardia occurred and was successfully treated with calcium administration. Risk factors for a potassium ≥6.5 mmol/L compared to those whose potassium remained below this value included:

  • length of ICU stay (P<0.001)
  • acute cerebral pathology (P=0.008)
  • previous succinylcholine use (P=0.026)

When a multivariate analysis was performed, both length of ICU stay and cerebral pathology remained significant. The critical threshold for length of ICU stay predictive of a post-succinylcholine potassium ≥6.5 was 16 days. This threshold was both sensitive and specific. There were 126 intubations before this 16 day threshold and only one of them had a post-succinylcholine potassium ≥6.5. There were 27 intubations after the 16 day threshold and 10 had a post-succinylcholine potassium ≥6.5. The median increase in this group was 1.9 mmol/L. One patient had an increase of almost 5 mmol/L.


Conclusion Length of ICU stay ≥16 days correlated with a greater than normal increase in serum potassium following succinylcholine administration. Risk of a serum potassium ≥6.5 mmol/L after succinylcholine included both an ICU stay ≥16 days and an acute cerebral pathology.



This was an especially well done study from an analytical perspective and it accomplished a lot given that the only way to carry it out was as an observational study. Now, I question whether all anesthesia providers in the USA would always use succinylcholine for intubations in the ICU, but that was the standard of care at the hospital in France when these data were collected and this study still has something to teach us. This is the first evidence I’ve seen that simply being immobile for long enough increases the risk for hyperkalemia following succinylcholine. We’ve long known that spinal cord injury patients that couldn’t move were at risk. But this is different. These were critically ill patients who were immobile because they were severely injured or unconscious; no spinal cord injury required.


One thing this study probably doesn’t tell us is the critical number of days of immobility (≥16 in this study) that places patients at risk for hyperkalemia after succinylcholine in your ICU. The reason I say this is twofold. First, the degree of immobility is likely an important factor. Perhaps all their patients were sedated to the point that they didn’t move at all and all your ICU patients are unsedated and move from time to time. Second, their patient population was mostly older men (median age 62 years, 72% male). To the extend that your patient population looks different than theirs, the critical length of immobility associated with the risk of hyperkalemia after succinylcholine may be shorter or longer. Please note, however, that the longer the immobility the higher the risk should still be true, no matter how different the patient population.


Lastly, I want to make some observations about figure 1 in this study which plotted the change in potassium after succinylcholine administration by the length of the patient’s stay in the ICU. There was a clear linear increase in potassium after succ as the length of ICU stay increased. The slope approximated 0.24 by my visual calculation. Not huge, but clinically significant over time. Changes in potassium in patients who’d been in the ICU less than 10 days had little variability; they tended to be closely clustered around the slope of the regression line. However, being in the ICU less than 16 days was no guarantee that patients wouldn’t get hyperkalemic after succ. Several patients in the 7 to 9 day range had increases in potassium of 1.5 to 2 mEq/L. So if they’d started with a K+ of 5 they would have ended up at 6.5 to 7 after succ. The variability in potassium increase got progressively larger the longer the length of the ICU stay. For example, one patient had almost no increase in potassium after succ at 28 days while another patient had a 5 mEq/L increase at 20 days.


This study gives us some solid evidence to better inform our choice of muscle relaxant for intubations in the ICU. If you use succ for intubation in your ICU, it may warrant measuring the pre and post succinylcholine potassium for a while in patients that have been there for a week or longer to see how large the increase in potassium is in your patients.

Michael A. Fiedler, PhD, CRNA

For potassium1 mmol = 1 mEq. This is not always the case, it depends upon the ionization state of the element in question.

© Copyright 2012 Anesthesia Abstracts · Volume 6 Number 8, August 31, 2012

Does intraoperative ketamine attenuate inflammatory reactivity following surgery? A systematic review and meta-analysis

Anesth Analg 2012;115:934-43

Dale O, Somogyi AA, Li Y, Sullivan T, Shavit Y


Purpose The purpose of this systematic review was to evaluate the effect intraoperative ketamine had on interleukin-6, an inflammatory biomarker, in surgical patients.


Background Major surgery is associated with a systemic inflammatory response and the release of proinflammatory cytokines (interleukin-6 [IL-6], interleukin-1β [IL-1 β], tumor necrosis factor α [TNFα]). Increased concentrations of inflammatory cytokines such as IL-6 have been associated with wall motion abnormalities and myocardial ischemia, perioperative complications, postoperative hyperdynamic instability, and have been correlated with postoperative morbidity and mortality in children undergoing open-heart surgery.


Several perioperative interventions have been attempted to reduce the inflammatory response and IL-6 concentrations. Multiple studies have examined the effects of opioids, inhaled anesthetics, local anesthetics, and ketamine. Most studies have mixed results; however, research results on local anesthetics consistently demonstrated an anti-inflammatory response. Ketamine has also been found to possess anti-inflammatory effects; however, the evidence has not been systematically evaluated to determine what effect intraoperative ketamine has on IL-6 concentrations.


Methodology This was a systematic review and metaanalysis of studies evaluating the effect intraoperative ketamine had on inflammation/immune modulation in surgical patients. The investigators were specifically interested in ketamine’s effect on IL-6 because this was the most consistently reported outcome. A standardized search strategy was used to identify and criteria used to grade the level of evidence of studies published up to October 13, 2011. Only randomized controlled studies were included. Metaanalysis statistics were used to evaluate the effect ketamine had on IL-6 concentrations measured within the first 6 hours postoperatively. 


Result Fourteen studies including 684 patients were eligible for evaluation. Of these studies, 8 involved cardiopulmonary bypass operations (CABG), 4 abdominal surgery, 1 thoracic surgery, and 1 cataract surgery. Only 6 of these studies were included in the meta-analysis (N = 331 patients; Table 1). A majority of studies evaluated CABG patients (n = 4), the other 2 included patients undergoing abdominal surgery (gastroplasty and hysterectomy). The authors judged the level of evidence to be high for all six of these studies. Most of the studies included a single bolus of ketamine ranging from 0.15-0.5 mg/kg [10.5 mg to 35 mg in a 70 Kg patient]. Only one study evaluated the effect of a ketamine-based technique as the sole anesthetic. That study compared ketamine 1-3 mg/kg at induction then 2-4 mg/kg/hr vs. sufentanil-based anesthesia with 0.25 to 1 µg/kg at induction then 0.5-2 µg/kg/h.


In all 6 studies, ketamine decreased IL-6 concentrations postoperatively. In general, ketamine had the greatest effect on IL-6 concentrations after cardiac surgery (Table 1 and Figure 1). In the two types of abdominal surgery included in the analysis, the authors of those studies found no significant difference in IL-6 concentrations postoperatively between ketamine or control groups. However, a significant effect of ketamine during abdominal surgery was seen when data was analyzed in this meta-analysis. No dose response effect was seen. There were no signs of publication bias in any of the reviewed studies.




Table 1. Studies Included in Metaanalysis

Population/sample size


IL-6 mean difference in pg/mL

1. CABG /n = 50 

Induction: ketamine 0.25 or 0.5 mg/kg

Control = saline 


2. CABG /n = 128

Ketamine-based anesthesia: 1-3 mg/kg induction then 2-4 mg/kg/hr

Sufentanil-based anesthesia: 0.25 µg/kg induction then 0.5-2 µg/kg/h


3. CABG /n = 50

Induction: ketamine 0.5 mg/kg

Control = saline


4. CABG /n = 31

Induction: ketamine 0.25 mg/kg

Control = saline


5. Abdominal /n = 22

Ketamine 0.15 mg/kg before incision

Control = saline


6. Abdominal /n = 36

Induction: ketamine 0.15 mg/kg

Control = saline




Figure 1. Mean Decrease Postoperative IL-6 After Perioperative Ketamine

Figure 1



Conclusion Intraoperatively administered ketamine significantly inhibited the inflammatory response in the early postoperative period, based on decreased IL-6 concentrations, in patients undergoing major surgery.



Use of ketamine perioperatively has seen a resurgence in recent years. Numerous studies have found it reduces postoperative pain and opioid consumption, and now we have some evidence after major surgery, that it also reduces the early postoperative inflammatory response as measured by IL-6 levels. In fact, one of the largest effects of ketamine on postoperative IL-6 levels was in a study which compared a sole ketamine anesthetic with a sufentanil-based anesthetic during cardiac surgery. These findings support the argument that ketamine has an anti-inflammatory effect. These are exciting findings and are sure to generate many studies in the future. The key “so what?” question we need to ask is, “does ketamine improve outcomes?” Theoretically it should, because a heightened inflammatory response has been associated with poorer outcomes, especially after major surgery.


It should be pointed out that the findings of this metaanalysis apply mainly to patients undergoing cardiac surgery. Only two studies examined patients having major abdominal surgery. I would be interested to see if a similar effect was seen after other less major surgery, and to find out what effect ketamine has on outcomes, such as wound infection, return of bowel function, cardiac morbidity, and chronic pain. Ketamine, even in subanesthetic doses, is not without side effects, and some patients may experience adverse psychomimetic effects or hyperdynamic responses. Therefore I think it is important we find out if ketamine does indeed improve outcomes.


From this analysis we cannot determine if there is a dose response with ketamine with regards to IL-6 levels. However, in most of the studies investigators used a subanesthetic dose of 0.15-0.25 mg/kg. Based on these findings, I would probably consider using the smallest possible dose, taking into consideration the patients comorbidities and the planned surgical procedure.

Dennis Spence, PhD, CRNA

The views expressed in this article are those of the author and do not reflect official policy or position of the Department of the Navy, the Department of Defense, the Uniformed Services University of the Health Sciences, or the United States Government.

© Copyright 2012 Anesthesia Abstracts · Volume 6 Number 8, August 31, 2012