Category Archives: General

Fatigue IV: Trauma Surgeons And Residents

The effects of fatigue on the surgeon have been looked at a number of times over the years. Most of this work focuses on resident physicians, however. Another problem with the majority of these studies is that they did not test the surgeon or resident on tasks that reflect real life practice.

A study from Arizona State University used a laparoscopic simulation that tested both psychomotor and cognitive skills that would be called on during real surgical procedures. In addition to the purely manual task of stacking varied sizes of rings using laparoscopic instruments, exercises were developed and validated that tested attention, tracking and other critical components. Monitored parameters included hand and tool movement, smoothness and economy of motion, and time required to complete the task. An overall proficiency score was calculated.

Five residents and nine attending physicians were tested. They were all given 4 practice sessions with the simulator before the study began. Sleep hours and caffeine use during call were recorded using a questionnaire. Each individual was then tested three times prior to being on call and three times post-call.

As would be expected, attending surgeons showed higher proficiency scores than residents both pre-call and post-call. However, both groups experienced significant declines in proficiency and significant increases in cognitive errors post-call. Interestingly, attending surgeons made 25% fewer cognitive errors post-call when compared to residents, and their psychomotor skills were unchanged. This suggests that the attendings were focused on skills at the expense of decision making.

Two other interesting items from this paper:

  • Errors increased exponentially with subjective reported fatigue in the attending surgeons. This means that a small amount of attending surgeon fatigue led to a large increase in errors. The implication is that the older attendings had less reserve, and that their greater skills and experience could be quickly overwhelmed.
  • Caffeine intake had no effect on motor skills or cognitive errors.

Bottom line: Fatigue from post-call sleep deprivation impedes psychomotor and cognitive functions, as well as performance. Residents are affected more than attending surgeons, but attending performance declines more rapidly as they grow fatigued. As any post-call surgeon knows, activities the day after call should be limited to the mundane to optimize patient safety.

In the next installment, we’ll look at the impact of poor sleep on our patients!

Reference: The effect of fatigue on cognitive and psychomotor skills of trauma residents and attending surgeons. Am J Surg 196(6):8133-820, 2008.

Fatigue III: Impact On Nurses

Although 8-hour shifts are the most common work arrangement around the country in all most occupations, they are a bit less common in nursing. Nurses have work and sleep patterns equivalent to prehospital providers. And critical care nurses probably have the most variable and punishing work patterns.

One may think that just increasing to a 12-hour shift is not that big of a deal. The nursing school at the University of Auckland performed their own survey of ICU nurses in two separate hospitals in New Zealand. They administered the Occupational Fatigue Exhaustion/Recovery Scale and evaluated differences in relation to a number of demographic variables.

Here are the factoids:

  • There were a total of 67 participants in the two hospitals and all worked 12-hour shifts.
  • Nurses at one hospital (A) worked mostly day or mostly night shifts and tended to be younger. Shifts were more mixed at the other (B).
  • About half of the nurses reported low to moderate fatigue acutely, and two thirds re-ported this level between shifts as well.
  • Factors that correlated with increased fatigue were younger age, fewer children, less years of experience, and less exercise.
  • Higher fatigue levels were reported at hospital A, which had the younger, less experienced nurses.

Bottom line: This is another survey study, but it does illustrate some common issues. Some factors could be changed by rearranging the shift structure to all day or all night shifts. Exercise was associated with less stress and could be encouraged. But the nature and pace of work in the ICU remains constant and is difficult to control for. Some strategies for positive change are listed on the next page of the newsletter.

In my next post, I’ll review the impact of sleep problems on trauma surgeons and residents.

Reference: Exploring the impact of 12-hour shifts on nurse fatigue in intensive care. Applied Nurs Res 50:151191, Dec 2019.

Fatigue II: Sleep Quality and Fatigue in Prehospital Providers

EMS providers across the country are assigned to a variety of schedules, ranging from shift work to continuous 24 hour service. Overnight duty, rotating schedules, early awakening and sleep interruptions are common. Unfortunately, there are not many studies on the effects of fatigue on EMS. I did manage to find an interesting study from last year that I’d like to share.

A group of about 3,000 providers attending a national conference were surveyed using 2 test instruments (Pittsburgh Sleep Quality Index (PSQI) and Chalder Fatigue Questionnaire (CFQ)). The PSQI measures subjective sleep quality, sleep duration, disturbances, use of sleeping meds and daytime dysfunction. The CFQ measures both physical and mental fatigue.

Only 119 surveys were completed, despite the fact that a $5 gift card was offered (not enough?). The most common certification was EMT-Basic (63%) and most had worked less than 10 years. Most were full-time, with most working 4-15 shifts per month. The following demographics were of interest:

  • Self-reported good health – 70%
  • Nonsmokers – 85%
  • Moderate alcohol or less – 62%
  • Overweight or obese – 85%

A total of 45% reported experiencing severe physical and mental fatigue at work, and this increased with years of experience. The sleep quality score confirmed this fact. Also of interest was the incidental finding of a high proportion of overweight or obese individuals. Sleep deprivation is known to increase weight, and increased weight is known to increase sleep problems, creating a vicious cycle.

Bottom line: This is a small convenience study, but it was enough to show that there is a problem with fatigue and sleep quality in EMS providers. Federal law mandates rest periods for pilots, truck drivers and tanker ship personnel. The accrediting body for resident physicians has guidelines in place that limit their time in the hospital. Prehospital providers perform a service that is just as vital, so it may be time to start looking at a more reasonable set of scheduling and work guidelines to protect them and their precious cargo.

In my next post, we’ll cover the impact of sleep loss on nurses.

Reference: Sleep quality and fatigue among prehospital providers. Prehos Emerg Care 14(2):187-193, April 6, 2010.

Fatigue: Sleep Deprivation Changes The Way We Make Risky Decisions

I’m expanding my series dealing with the issues surrounding lack of sleep. As you all know, trauma professionals are expected to perform even if they have not had adequate sleep. This can occur with certain shift schedules, long periods of work, or due to call schedules and duration of call. What do we really know about the effects of sleep deprivation on us?

For the next few weeks I’ll be writing about the effects of fatigue on trauma professionals, including prehospital providers, residents, surgeons, and nurses. And I’ll finish up with some new research on the effects on our patients.

In this post, we’ll talk about decision making. Neuroscientists at Duke looked at how we approach risky decisions when we are sleep deprived. A total of 29 adults (average age 22) were studied. They were not allowed to use tobacco, alcohol and most medications prior to sleep deprivation, which lasted for 24 hours. They were given a risky decision making task (a controlled form of gambling), and two other tests while in a functional MRI unit to watch areas of brain activation.

The researchers found that, when well rested, the subjects had a bias toward avoiding loss in the gambling test. After a single night of sleep deprivation, this shifted to pursuing gain. The MRI also showed an increased activity in the reward anticipation parts of the brain. Overall decreased vigilance was noted, but this did not correlate with the shift away from risk avoidance.

Bottom line: Sleep deprivation appears to create an optimism bias. Fatigued individuals act like positive outcomes are more likely and negative consequences are less likely. One of the most common and important things that trauma professionals do is to make decisions that may affect patient outcome (e.g. choose a destination hospital, intubate, order and interpret a test, move to the operating room, choose a specific operative procedure). We all have a set of thresholds that help us come to the “right” decision based on many variables. It appears that a single night of sleep deprivation has the potential to skew those thresholds, potentially in directions that may not benefit the patient.

In the next post, I’ll turn my attention to the impact of sleep loss on prehospital providers.

Reference: Sleep deprivation biases the neural mechanisms underlying economic preferences. J Neuroscience 31(10):3712-3718, March 9, 2011.

Best Of AAST #6: Timing Of Venous Thromboembolism Prophylaxis

Venous thromboembolism (VTE) and pulmonary embolism (PE) have caused major problems for trauma professionals for at least 50 years. Interestingly, despite advances in chemical and mechanical prophylaxis, the mortality rates for both have remained about the same.

The group at St. Joseph Mercy Hospital in Ann Arbor looked at the timing of start of VTE chemoprophylaxis. They were curious as to whether the start time made a difference in mortality. They reviewed a collaborative database with 12 years of data, tallying information for all trauma patients who were admitted for at least 48 hours.

Here are the factoids:

  • Over 89,000 patients were analyzed; 1.8% developed VTE and 1.9% died (?)
  • Delay in starting chemoprophylaxis increased the risk of VTE (see figure)
  • Delaying chemoprophylaxis beyond 48 hours was associated with increased mortality and increased incidence of VTE

The authors concluded that early initiation of chemoprophylaxis reduces mortality and thrombotic complications.

Here are my comments: Unfortunately, I’m not entirely clear about the details of the abstract. This frequently happens because the authors have to strain to fit all of their ideas in a finite amount of space.

First, it’s a large database study, so it’s difficult to ensure that all the factors you want to study have been included in it. Somebody else designed it years ago, so you get what you get.

I’m a little confused about the incidence of complications and death. They are both about the same number (1.8%). Typically, VTE incidence is a few percent and death from PE is less than 1%. The death number seems high, unless it includes some other type of death.

The VTE incidence vs time graph is very interesting, although the goodness of fit looks a little off toward the right side. It looks like it could easily be a little lower.

Finally, segregating time periods into two 24-hour periods (0-24 hours, 24-48 hours)and one 72-hour plus one (48-120+ hours) seems like it might bias your data. The longer that last period, the greater chance that each patient will develop VTE or die.

Overall, the numbers in Table 1 are noted to be statistically significant, but clinically they appear to be very similar.

Here are some questions for the presenter:

  • Please explain the mortality numbers (1.9%). What did these patients die of? A pulmonary embolism? Something unrelated? This number seems high, since it is equal to your VTE incidence.
  • Tell us about the risk adjustment you used to calculate mortality rates. What patient factors were available to you? Are there others that might have been helpful to have in the database?
  • What tool did you use to fit the curve in Figure 1? The right side looks considerably higher than the data bars would suggest. Please be sure to explain all of the statistical techniques you used, as they were not fully covered in the abstract.
  • What was the impact of cramming 3 days of data into your last cohort? Wouldn’t this be expected to yield higher incidences of VTE and death?

I agree that VTE prophylaxis is best started early, but I need a wee bit more information. I’m intrigued by the paper, but I think you will have to spend some time explaining how you designed the analysis so we can all understand.

Reference: Association of timing of initiation of pharmacologic venous thromboembolism prophylaxis with outcomes in trauma patients. AAST 2020, Oral Abstract #14.