Category Archives: Abstracts

EAST 2019 #3: Chest Tube vs Pigtail

I love stuff about chest tubes. There are so many opinions and so little data to back them up. And now here’s another EAST 2019 Annual Assembly paper from the University of Arizona at Tucson on chest tubes! The traditional dogma, and something that I’ve promoted for some time, is that the only size chest tube that should be used for hemothorax is big (36 Fr) or bigger (40 Fr). There have been a few abstracts and published papers over the past 7 years that are trying to change this assumption. Will they be successful?

The first work on this was a paper published in 2012 by this same group in Tucson. It was a prospective study that included 36 patients with pigtails and 191 with 32 Fr – 40 Fr chest tubes over 30 months. Average initial drain output was the same, and there were no differences in tube in time, complications, or failure rate.

A related abstract was then presented by this group at the 2013 EAST Annual Assembly, but it doesn’t look like this one got published. It was a small, prospective study that enrolled 40 of 72 eligible patients over 20 months and compared pigtail catheters vs 28 Fr chest tubes. They found that chest wall and tube site pain was less with a pigtail, and that failure and complication rates, tube in time, and hospital stay were the same.

And then in 2017 more related work was presented at EAST from the group, and was later published in the World Journal of Surgery. This study was the culmination of 7 years of experience, and included nearly 500 subjects. Once again, initial drainage output was the same, as were complications and failure rate. The authors concluded that a multi-center trial was need to provide additional support.

And that brings us up to EAST 2019. Now the authors are presenting a single-center study comparing 14 Fr pigtail vs 28-36 Fr chest tubes for hemothorax and pneumthorax. What’s different about this one? For the first time, the subjects were randomized between pigtail and chest tube in an effort to eliminate selection bias.

Here are the factoids:

  • A total of 43 patients were enrolled, but the number excluded was not given
  • Although baseline characteristics of the two groups were identical, several differences approached clinical significance: percent blunt trauma, flail chest, insertion day, and initial chest tube output
  • The authors concluded that there were no differences in initial chest tube output, failure rate, tube days, and lengths of stay. However, perceived pain was less.
  • They again noted that a multi-center trial should be performed to confirm these results

Here are some questions for the authors and presenter to consider in advance to help them prepare for audience questions:

  • What’s new and different with this study? The University of Arizona – Tucson has been studying pigtails since 2009. Tell us about the progression of this work and how the current study fits in.
  • How many patients were excluded? This is very important, especially if this number is high. What were the exclusion criteria exactly?
  • What did your power analysis show? The overall enrollment numbers are low, which may throw your statistics into doubt. This is especially true since your primary outcome showed that pigtail and chest tube outputs were the same but with a p=0.06! More patients may have helped show the desired difference.
  • Were the pigtail and chest tube groups really “similar?” There were more penetrating injuries in the chest tube group. Could this have an impact on clotted vs non-clotted blood in the chest and the ability of a pigtail to drain it? And the median pigtail insertion date was 1.5 days later than for chest tubes, which is clinically significant. Could this allow time for defibrination of the hemothorax, resulting in better drainage?
  • And what’s next? Will I see you again at EAST 2020 or 2021 with a larger prospective study? Or a multi-center one?

I’m looking forward to hearing this one in person!

References:

  • A single center prospective randomized study comparing the effectiveness of 14 French percutaneous catheters (pigtail) versus 28-36 French chest tube in the management of traumatic hemothorax/hemopneumothorax. EAST 2019 Paper #13.
  • EAST abstract presentation 2013.
  • EAST abstract presentation 2017.
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EAST 2019 #2: Utilization of Damage Control Laparotomy

The next paper presentation I’ll review from the upcoming EAST Annual Assembly is from a consortium of six US trauma programs, and appears to be under the direction of faculty at the McGovern Medical School in Houston. They recognized that rates of damage control laparotomy (DCL) vary widely throughout the US. In part, this is due to the lack of hard and fast indications for the application of this procedure. This procedure is used in cases where patient physiology (or trends in that physiology) would suggest that persisting with an open body cavity would lead to hypothermia, coagulopathy, additional injury, or death.

This study entailed the prospective review of every DCL performed at the centers over a one year period. Each was adjudicated by a majority faculty vote as to whether it would have been safe and appropriate to perform a definitive laparotomy (DL) instead. DL means that all injuries are fixed and the abdomen is closed.

Here are the factoids:

  • 872 trauma laparotomies were performed: 209 DCL and 639 DL. There were 24 intraoperative deaths.
  • There was no change in DCL rate compared to historical controls for 5 of the 6 centers (see diagram)
  • One center had an initial reduction in DCL rate, but this disappeared throughout the rest of the study
  • The voting group found consensus in recommending DCL with hemodynamic instability or if packing was required, but could not agree on the need for second look procedures

Overall, this intervention (reviewing each and every damage control procedure immediately after) did not decrease the DCL rate as hoped. The authors cited the second look laparotomy disagreement as a possible target to improve results.

Here are some questions for the authors and presenter to consider in advance to help them prepare for audience questions:

  • All DCLs are not the same. Six different centers were studied, each with their own DCL popluation. What was the blunt:penetrating mix for each? What were the specific mechanisms and injuries sustained? ISS? It could be that the study group was not homogeneous, making it more difficult to judge appropriateness.
  • Was the study powered well enough to detect differences? The total number of DCL cases was only 209, or 35 per center. And of course, some had more, some less. In our original DCL paper from Penn, the clinical significance first showed up only in the subset of most severely injured penetrating injury patients. Did you have enough patients?
  • What exactly was the intervention that would drive down the DCL rate? Although this is (kind of) a prospective project, the analysis of each case and the consensus vote took place after each procedure. Was this done at each institution, or only by the research group at the mother ship? How did the results get disseminated to all surgeons so that they could apply the findings to their next trauma laparotomy?
  • Look at the outlier. This is always valuable. Why was center #4 so much lower at the beginning of the study period compared to the one year historical control? Were their laparotomy numbers lower? Patient/injury mix different? Did you interview that group to see what their insights were? This is one of the most interesting findings, in my opinion.

I’ll be sitting in the front row for this one!

Reference: Better understanding the utilization of damage control laparotomy: a multiinstitutional quality improvement project. EAST 2019, Paper #12.

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EAST 2019 #1: Predicting Outcome After Brain Injury

Here’s the first abstract I’ll review from the EAST 2019 Annual Assembly in January.

This one comes to us from the University of Arizona system, and specifically from Tucson. The senior author has an interest in traumatic brain injury (TBI) and geriatric trauma, so it’s not surprising to see this abstract that fuses the two. The aim was to create a new tool to predict mortality in patients who had sustained a TBI.

The authors devised a score, the Brain Trauma Outcome Score (BTOS) using three variables: age, injury severity score (ISS), and presence of blood transfusion. Furthermore, this was used to create a Brain Trauma Outcome Score (BTOS), by dividing the BTOS by the GCS. These equations were developed and tested using data sets from two years worth of TQIP data. I know, lots of acronyms, but stay with me. After generating the equations for GTOS and BTOS from one TQIP dataset and testing against another, both of these systems were checked for discriminatory power by generating receiving operator characteristic curves.

The authors found that the tested BTOS was better at predicting mortality than the tested GTOS. They concluded that “BTOS can accurately predict in-hospital mortality in all TBI patients.” Seems like a pretty bold assertion.

Here are some questions for the authors and presenter to consider in advance to help them prepare for audience questions:

  • Be aware that some typos crept into the final copy. When preparing abstracts, try not to use special characters (i.e. +) as they may not be generic enough for the commercial printing software used to prepare final copy. This is similar to avoiding video or links to YouTube videos in slide sets. I was able to figure out what the question marks really were (I think), but make sure the audience does, too.
  • Why did you even think to create this model? Some new “systems” are just wild guesses, and sometimes it’s even possible to find one that appears to have a significant correlation with reality. What was the rationale that prompted you to combine ISS, age, blood, and GCS? Did your clinical experience suggest this? Papers on related prediction systems? Then what?
  • Is validating your test data using other patients from the same dataset legitimate? Shouldn’t they be very similar since they are in the same 2-years of data? This could make the system less accurate when applied to a very different patient cohort.
  • The GCS range studied was very high and narrow. If I read the abstract correctly, the median was 14-ish with a range from 12-15. These are mostly mild TBIs, so why were they dying anyway? And if the formula for GTOS was derived using predominantly mild TBI data, how can it possibly work well for moderate and severe? And I still worry that patients were dying of problems unrelated to TBI.
  • Make sure you clearly explain your methods to the audience. Some are not well versed in ROC curves, and many will not understand the nuances and potential pitfalls of developing and validating numerical systems like this. It’s easy to lose them, so make sure you are clear and concise in your explanations.
  • How do you see a system like this being used in the future? It’s nice to have some appreciation of the practicality, and an assurance that this isn’t just an academic exercise.

I enjoyed the abstract, and look forward to hearing it in person next month!

Reference: The Brain Trauma Outcome Score (BTOS): Estimating mortality after a traumatic brain injury. EAST 2019, Paper #6.

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Starting Next Week: EAST 2019!

The 32nd Annual Assembly of the Eastern Association for the Surgery of Trauma (EAST) is just around the corner. The meeting starts January 15 in Austin, TX.

I traditionally choose some of the abstracts to presented that I find particularly interesting. I’ll dissect them here on the blog, and provide suggestions to the authors on how to prepare for questions they might receive from the audience at the meeting.

Starting next Monday, and continuing through the meeting in Mid-January, I’ll be posting one critique per day. Tune in and enjoy!

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Best of AAST #11: The Need For Trauma Intervention Score (NFTI)

The Trauma Measurement Workgroup at Baylor University in Dallas has been working on a new indicator for identifying major trauma. In a paper published in the Society of Trauma Nursing last year, they determined that six trauma registry variables best identified these patients:

  • transfusion of packed cells within 4 hours of arrival
  • discharge from ED to OR within 90 minutes of arrival
  • discharge from ED to interventional radiology
  • discharge from ED to ICU with a stay > 3 days
  • mechanical ventilation within 3 days, not including OR or procedures
  • death within 60 hours of arrival

Traditionally, Injury Severity Score (ISS) has been used to measure anatomic injury, the Revised Trauma Score (RTS) to quantify physiologic derangement, and their combination (TRISS) to estimate survival.  The authors postulate that physiologic reserve is another determinant of survival, and that NFTI might provide a way to quantify this reserve. One of the QuickShot presentations at the AAST meeting demonstrates how the authors applied this metric.

A multi-institutional data collaborative collected information on more than 88,000 across 35 trauma centers. A complicated mathematical and statistical analysis was carried out, testing how well high ISS (>15), low RTS (<4), and NFTI+ (at least one NFTI variable) predicted mortality, complications, full trauma team activation, length of stay, and procedures performed within 3 days of arrival.

The authors found that NFTI was significantly better at predicting all the outcome variables except full trauma activation than ISS or RTS. And it was still pretty good at that one.

Bottom line: So what does all this mean? The design and analysis of all the numbers is sound. The only thing I take issue with is the assumption that NFTI reflects the “reserve” that a patient has available to combat serious injury. The authors postulate that NFTI is not affected by frailty and comorbidities like ISS and RTS are. I have not seen the manuscript, so perhaps the authors explain the rationale there. But it seems like a stretch. 

What happens if we remove that assumption? Then this study becomes a comparison of a new way to predict resource utilization and/or survival vs ISS and RTS. It uses future variables (as does ISS), so it is difficult to apply this information on patient arrival to treat them any differently, until the first NFTI factor is triggered. But it does predict them well. I think there is considerable potential for NFTI, but we just need more work to make it more useful as early as possible.

Reference: The need for trauma intervention (NFTI) defines major trauma more accurately than injury severity score (ISS) and revised trauma score (RTS): data from a collaboration of 35 adult trauma centers. QuickShot presentation #9, AAST 2018.

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