Tag Archives: abstract

Best Of AAST 2021: Individual Surgeon Outcomes In Trauma Laparotomy

Trauma programs use a number of quality indicators and PI filters to evaluate both individual and system performance. The emergent trauma laparotomy (ETL) is the index case for any trauma surgeon and is performed on a regular basis. However, this is one procedure where individual surgeon outcome is rarely benchmarked.

The trauma group in Birmingham AL performed a retrospective review of 242 ETLs performed at their hospital over a 14 month period. They then excluded patients who underwent resuscitative thoracotomy prior to the laparotomy. Rates of use of damage control and mortality at various time points were studied.

Here are the factoids:

The chart shows the survival rates after ETL at 24 hours (blue) and to discharge (gray) for 14 individual surgeons.

  • Six patients died intraoperatively and damage control laparotomy was performed in one third.
  • Mortality was 4% at 24 hours and 7% overall
  • ISS and time in ED were similar, but operative time varied substantially (40-469 minutes)
  • There were significant differences in individual surgeon mortality and use of damage control

The authors concluded that there were significant differences in outcomes by surgeon, and that more granular quality metrics should be developed for quality improvement.

Bottom line: I worry that this work is a superficial treatment of surgeon performance. The use of gross outcomes like death and use of damage control is not very helpful, in my opinion. There are so, so many other variables involved in who is likely to survive or the decision-making to consider the use of damage control. I am concerned that a simplistic retrospective review without most of those variables will lead to false conclusions.

It may be that there is a lot more information here that just couldn’t fit on the abstract page. In that case, the presentation should clear it all up.  But I am doubtful.

We have already reached a point in medicine where hospitals with better outcomes for patients with certain conditions can be identified. These centers should be selected preferentially to treat stroke or pancreatic cancer, or whatever there benchmark-proven expertise is. It really is time for this to begin to trickle down to individual providers. A specific surgeon should be encouraged to do what they are demonstrated to be really good at, and other surgeons should handle the things the first surgeon is only average at.

But I don’t think this study can provide the level of benchmarking to suggest changes to a surgeon’s practice or the selection of a specific surgeon for a procedure. A lot more work is needed to identify the pertinent variables needed to develop legitimate benchmarks.

Here are my questions for the presenter and authors:

  • Show us the details of all of the variables you analyzed (ISS, NISS, time in ED, etc) and the breakdown by surgeon.
  • Are there any other variables that influence the outcome that you wish you had collected?
  • There were an average of 17 cases per surgeon in your study. Is it possible to show statistical significance for anything given these small numbers?

The devil is in the details, and I hope these come out during the presentation!

Reference: IT’S TIME TO LOOK IN THE MIRROR: INDIVIDUAL SURGEON OUTCOMES AFTER EMERGENT TRUMA LAPAROTOMY. AAST 2021, oral abstract #38.

Best Of AAST 2021: Validating The “Brain Injury Guidelines” (BIG)

The Brain Injury  Guidelines (BIG) were developed to allow trauma programs to stratify head injuries in such a way as to better utilize resources such as hospital beds, CT scanning, and neurosurgical consultation. Injuries are stratified into three BIG categories, and management is based on it. Here is the stratification algorithm:

And here is the management algorithm based on the stratification above:

The AAST BIG Multi-Institutional Group set about validating this system to ensure that it was accurate and safe. They identified adult patients from nine high level trauma centers that had a positive initial head CT scan. They looked at the the need for neurosurgical intervention, change in neuro exam, progression on repeat head CT, any visits to the ED after discharge, and readmission for the injury within 30 days.

Here are the factoids:

  • About 2,000 patients were included in the study, with BIG1 = 15%, BIG2 = 15%, and BIG3 = 70% of patients
  • BIG1: no patients worsened, 1% had progression on CT, none required neurosurgical intervention, no readmits or ED visits
  • BIG2: 1% worsened clinically, 7% had progression on CT, none required neurosurgical intervention, no readmits or ED visits
  • All patients who required neurosurgical intervention were BIG3 (20% of patients)

The authors concluded that using the BIG criteria, CT scan use and neurosurgical consultation would have been decreased by 29%.

Bottom line: This is an exciting abstract! BIG has been around for awhile, and some centers have already started using it for planning the management of their TBI patients. This study provides some validation that the system works and keeps patients safe while being respectful of resource utilization. 

My only criticism is that the number of patients in the BIG1 and BIG2 categories is low (about 600 combined). Thus, our experience in these groups remains somewhat limited. However, the study is very promising, and more centers should consider adopting BIG to help them refine their management of TBI patients.

Reference: VALIDATING THE BRAIN INJURY GUIDELINES (BIG): RESULTS OF AN AAST PROSPECTIVE MULTI-INSTITUTIONAL TRIAL. AAST 2021, Oral abstract #25.

Best Of AAST: Delayed Treatment Of Blunt Carotid And Vertebral Injury

I recently published a series on blunt carotid and vertebral artery injury (BCVI). Today, I’ll review an AAST abstract that details the results of a multicenter study on the timing of medical treatment of this condition. This typically takes the form of anti-platelet agents, usually aspirin.

The trial collected prospective, observational data from 16 trauma centers. Patients had to receive medical therapy at some time after their injury or they were excluded. The stroke consequences of early vs late medical therapy were evaluated, where late was defined at > 24 hours.

Here are the factoids:

  • There were 636 BCVI included in the study
  • Median time to first medical therapy was 11 hours in the early group and 62 hours in the late group
  • ISS was higher in the delayed group (26 vs 22); although this was “statistically significant”, it is probably not a clinically significant difference
  • There was no increase in stroke rate with later administration of medical treatment

Bottom line: This is a very interesting study. We always worry about missing BCVI (see my previous post here), and now we know a little more about what happens if we do. The authors suggest that the stroke rate does not go up if medical management is delayed, say for some other potential bleeding issue.

This is a reasonably large data set, but the key thing to consider is the time frame observed. The median delay to medical management was only about 2.5 days. Were there any strokes involved in the patients with much longer delays? That is the real question. And were there any strokes that occurred despite early/immediate medical management?

The descriptive statistics and simple analyses presented do not provide all of the information we need. A stoke is a very significant adverse event for the patient. Statistical means are fine, but information on the specific patients who suffered one is necessary to truly understand this issue.

Here is my question for the presenter and authors:

  • Please break down the details on all patients who suffered a stroke. It will be very interesting to see if there were any in the early group and if there was a trend toward stroke in the very late tail data.

Reference: DOES TREATMENT DELAY FOR BLUNT CEREBROVASCULAR INJURY AFFECT STROKE RATE?: AN EAST MULTICENTERTRIAL. AAST 2021, Oral abstract #23.

Best Of AAST 2021: Liposomal Bupivacaine For Rib Fractures

The mainstays of rib fracture management are pain control and pulmonary toilet. The pain part of the equation can be managed in many ways, using topical, oral, IV, and injectable medications.

Rib blocks have been a mainstay for achieving some degree of local pain control. Classically, xylocaine was injected in the area around the costal nerve at or proximal to the fracture site. Then we found that if we combined the anesthetic agent with epinephrine, we could prolong the effect. New, longer-acting agents came around, and we could achieve a longer duration of action.

Then there is the new kid on the block: liposomal bupivacaine, also known as Exparel in the US.  The manufacturer was able to take molecules of bupivacaine and encapsulate them in a lipid membrane. When injected, these little liposomes slowly release their cargo, with a more prolonged anesthetic effect. Allegedly.

Sounds great! But does it work? The group at University of Cincinnati designed a prospective, double-blinded, randomized placebo control study of liposomal bupivacaine vs saline injection for pain control in up to six rib fractures. Subjects had significant injury as measured by their inability to achieve at least 50% of the desired inspiratory capacity. The authors monitored a number of respiratory parameters, as well as the pain score.

Here are the factoids:

  • Two cohorts of 50 patients were recruited, one received liposomal bupivacaine in up to six rib fractures, and the other received saline injections
  • The bupivacaine group achieved higher incentive spirometry volumes over the first two days, by about 200 cc
  • There was no change in daily pain scores in either group
  • Both groups showed a similar decrease in opioid use over time
  • Hospital and ICU lengths of stay were the same, and there were no complications or adverse events

Bottom line: Hmm. What’s going on here? There is a moderate amount of literature out there that does indicate a positive effect from liposomal bupivacaine in other conditions. But there are also some blinded, randomized studies that fail as well. So there are three possibilities:

  1. Liposomal bupivacaine isn’t a panacea, and works better in some situations than others
  2. This study failed to show a real difference for some reason
  3. A combination of both

This is a relatively small study, and the authors were not able to share their power analysis. They did not state if the spirometry volumes were significantly different, although I’m not sure 200 cc is clinically relevant. Maybe. But pain scores remained similar and opioid use declined as expected in both. 

These kinds of studies can be important. The difference in cost between injecting liposomal bupivacaine ($19 / ml) vs regular bupivacaine (10 cents / ml) vs saline/nothing (free) is striking. The premium price for the liposomal form needs to have a clear benefit or a cheaper product should be used.

Here are my questions for the presenter and authors:

  • Was your study big enough to show a result? Show us your power analysis.
  • How significant was the incentive spirometry result. Was the difference clinically noticeable?
  • What is your takeaway for this study? Your conclusion parrots the results. What will you do differently now, if anything?

Reference: INTERCOSTAL LIPOSOMAL BUPIVACAINE INJECTION FOR
RIB FRACTURES. AAST 2021, Oral abstract #20.

Best Of AAST 2021: Identifying Risk For Elderly Falls

Over the past 20 years, falls have become the most common mechanism of injury at most trauma centers. In fact, many centers count twice as many falls as motor vehicle crashes! The problem with working in a trauma center is that we tend to see patients at risk for falls only after they have fallen.

The group at Butterworth Hospital attempted to determine if there was a way to identify patients at risk for falls earlier. They postulated that many of these patients may have experienced a fall within the past year, identifying them as at high risk for yet another. They retrospectively reviewed their trauma registry data for a three year period. Specifically, they wanted to identify how many of those had suffered earlier falls and what happened to them over time.

Here are the factoids:

  • A total of 597 patients were also admitted due to a fall during the year prior to their index admission
  • Only 2% had falls prevention teaching after the previous admission
  • About a third of patients fell again within a year after the index admission, and 20% were admitted again
  • The patients were assessed using the Hester-Davis score (see below), and patients who were identified by it as high risk were more likely to be readmitted or die
  • Overall mortality at 12 months was about 20%

The authors were surprised that so many of their falls patients had been previously admitted for a fall. They recognized that it presents a major prevention opportunity, and recommend these patients undergo some type of activity before and/or after discharge.

Note: The Hester Davis Fall Risk Scale (HDFRS) includes factors of age, date of last known fall, mobility, medications, mental status, toileting needs, volume/electrolyte status, communication/sensory, and behavior with the option to choose multiple options per risk category; a score of seven to ten indicates low fall risk, eleven to fourteen indicates moderate fall risk, and greater than fifteen indicates high fall risk.

Bottom line: This is a straightforward single-hospital registry study. Even though it reflects the experience of a single rural trauma center, the results are applicable to most others. It confirms that any fall in the elderly should be considered a sentinel event which has a good chance leading to death within a year. 

Here’s the way I see it:

“You fall, you die”

It is very important that every trauma center identify these patients when they arrive, and apply prevention efforts while in the hospital or hook them up with activities after discharge. And if you don’t have such a program included in your injury prevention activities, you should! It’s the most common mechanism seen by trauma centers, hands down!

I have only one suggestion for the presenter and authors:

  • The concept of being “at risk” was not clear to me. Did this mean that you looked back one year for each admission to see if there was an admission for a fall? Or did you just get the history of a fall from the previous admission? It looks like you identified an index admission, then looked back a year to see if the patient should be included in this study. Then you looked forward a year to see if there was yet another admission and/or death. Is this correct? Please clarify during your presentation at the meeting.

Reference:  FALL RISK IDENTIFICATION THROUGHOUT THE
CONTINUUM OF CARE. AAST 2021, Oral abstract #18.