All posts by TheTraumaPro

Best Of EAST #8: Early vs Late Full Anticoagulation In TBI

Trauma professionals are always reluctant to anticoagulate TBI patients with demonstrated blood in their head. In recent years, we’ve become more comfortable providing prophylactic doses of low molecular weight heparin after a suitable period. This is typically 24-48 hours after a stable head CT in patients with select types of intracranial hemorrhage (ICH) who are at increased risk for venous thromboembolism.

But what about therapeutic dose anticoagulation in these patients? Let’s say that you have a patient with ICH who has developed a significant pulmonary embolism (PE)? Is is safe to give full dose anticoagulation? And if so, when?

The group at Shock Trauma in Baltimore attempted to answer this in one of the EAST Quick Shot presentations scheduled for this week. The did a retrospective review of 4.5 years of their own data on these patients. They specifically selected patients who had both ICH and PE and compared those who received full anticoagulation within 7 days of injury vs those who were dosed after 7 days. Outcomes studied included death, interventions for worsening ICH, and pulmonary complications.

Here are the factoids:

  • A total of 50 patients had both ICH and PE, but only the 46 who received therapeutic anticoagulation were analyzed
  • 19 patients (41%) received early anticoagulation, and 27 received it late (59%)
  • There were 4 deaths in the early group (2 from the PE, 1 from multi-system organ failure, 1 from the TBI) vs none in the late group, and this was statistically significant
  • 3 patients in the early group (18%) vs 2 in the late group (7%) had an increase in their ICH (p=0.3), and none required intervention

The authors concluded that their study failed to show any instances of clinically significant progression of ICH after anticoagulation, and that it is not associated with worse outcomes, even if started early. Thus they recommend that ICH should not preclude full anticoagulation, even early after injury.

My comment: I always say that you shouldn’t let one paper change your practice. Even a really good one. In order to ensure that you are providing the best care, more work must always be done to confirm (or refute) the findings of any provocative research. And this little Quick Shot, with little opportunity for questions from the audience, should definitely not change it!

The major issues to consider here are common ones: 

  • This was a retrospective study and it does not appear that any guideline was followed to determine who got early vs late anticoagulation. So who knows what kind of selection bias was occurring and how the surgeon decided to prescribe anticoagulation? It’s very possible that patients with a “bad CT” were put into the late group, and the not so bad ones in the early group. This would bias the results toward better outcomes in the early anticoagulation group.
  • It’s also a very small study that is extremely underpowered. The authors comment on the fact that the outcomes of the early group were not worse than the late group. However, looking at their sample size (46) shows that they would only be able to show differences if they were about 5x worse in the early group. They would realistically need about 350 total patients to truly show that the groups behaved the same. Their small numbers also preclude saying that there were no ICH progressions. There very well could have been if 300 more patients were added to the series.
  • And isn’t death a significant outcome? The authors indicated that 2 of the 4 deaths were a result of the PE. Yet there was a significant association (p=0.02) of increased death in the early anticoagulation patients that can’t be discounted.

Bottom line: It’s way too early to consider giving early anticoagulation to patients with ICH and pulmonary embolism. It may very well be shown to be acceptable, eventually. But not yet. And a much bigger prospective study will be required to confirm it.

Reference: Therapeutic anticoagulation in patients with traumatic brain injuries and pulmonary emboli. EAST Annual Assembly Quick Shot #7, 2020.

Best Of EAST #7: Is There A Relationship Between Number Of Transfusions And Infection?

It has long been known that blood transfusion decreases immunocompetency for a period of time. This has been taken advantage of in transplant surgery for decades. And blood transfusions are used liberally in major trauma. So could blood transfusion make it more likely for a trauma patient to suffer complications such as pneumonia, sepsis, and surgical site infections?

The group at the Massachusetts General Hospital explored this possibility. The analyzed four years of TQIP data, examining patients who received blood transfusions within four hours of arrival. They excluded transfers in, patients with incomplete transfusion counts, and those who died within 48 hours.

They focused on pneumonia, sepsis, and surgical site infections and statistically controlled for demographics, comorbidities, injury severity, and surgical/procedural interventions.

Here are the factoids:

  • A million patients (!) were reviewed and about 41,000 met study criteria
  • The odds ratio of infectious complications increased from 1.23 after 2 units to 4.89 after 40 units
  • Each additional unit after 40 increased the odds of an infection by another 4.9%

The authors concluded that blood transfusion is associated with a dose dependent risk of infectious complications and that patients should be resuscitated to achieve prompt hemorrhage control (really?).

My comment: Well, this certainly looks fairly straightforward. Of course, it suffers from the usual drawbacks of massaging large databases. And remember, it shows an association, not cause and effect. How can we tease out whether the higher infection risk is due to badly hurt patients who need major surgery and prolonged ICU stays with pneumonia? The authors have tried to reduce this as much as possible using logistic regression. Unfortunately, many of the variables are very interdependent and I don’t believe the methods can fully overcome this. And there may be other factors not available for analysis in the TQIP data.

Here is my only question for the authors and presenter:

    • How can you be sure that you have fully controlled for the key variables that might influence your final analysis? Yes, you considered demographics, three listed comorbidities (cirrhosis, diabetes, and steroid use), injury severity, and some interventions. But might there be other factors not listed and maybe not even in the TQIP data? Ideas?

This is one of those papers that makes you say “hmm”. But don’t we always try to stop the bleeding promptly. I’m not sure what alternative we have to giving blood.

Reference: Overtransfusion comes at a significant cost: the dose-dependent relationship between blood transfusions and infections after major trauma. EAST Annual Assembly abstract #26, 2020.

Best Of EAST #6: Uber / Lyft vs Drunk Driving

Ride share services like Uber and Lyft are now pretty much ubiquitous. It’s so easy to get a ride these days one would think that the incidence of car crashes due to drunk driving should be declining, right?

Well, nobody knows for sure. But the group at Tulane decided to look at their own data for alcohol-related car crashes over a seven year period. They also combed regional traffic databases for more information and compared the data from pre- to post- arrival of ride share services.

Here are the factoids:

  • There were 1474 patients involved in alcohol-related crashes (ARC)
  • The proportion of alcohol-related ARCs decreased significantly from 39% to 29%
  • The overall annual incidence of fatal ARCs seen at Tulane decreased significantly from 11.6 to 5, and also decreased significantly within the region
  • However, the incidence of ARCs only decreased within the 21-24 year age group(!)

My comment: This is very interesting work! The statistics appear to be sound and the number sufficiently large. It shows that it might be possible to decrease drunk driving injuries using methods other that the usual prevention efforts. It is puzzling, though, that the effect is only seen in a very narrow age group in the population. Practically everyone can use a ride-hailing app these days. Even I do!

Here are my questions for the authors and presenter:

  1. How do you explain the very narrow age-range that appears to be affected? Remember, this study shows an association, not cause and effect. Could it be that something else is reducing alcohol-related crashes in this specific age group, and it has nothing to do with ride share availability? What else could it be?
  2. How can this decrease in 21-24 year olds hold when there was such a significant decrease in overall alcohol-related crashes? Was everyone driving around New Orleans in that age group? Otherwise, how can this be explained?

I am fascinated by this study. But it’s going to be difficult to separate out other confounding variables and causes to be able to point definitively to any benefit from ride share services.

Reference: Do ride sharing services affect the incidence of alcohol-related motor vehicle collisions? EAST Annual Assembly abstract #22, 2020.

Best Of EAST #5: Keeping Blood From Going Bad

What goes around comes around. Whole blood was the only transfusion product available until about 60 years ago, when the whole blood banking system switched to fractionating blood products. Now we are discovering the benefits of whole blood again. The military has been using fresh whole blood for some time. As civilians, we’ve had less access to whole blood. But once obtained, it must be used within 21 days. This is half the storage time for the usual bag of packed red cells, and may result in some waste of this valuable product.

The group at the University of Cincinnati wondered if fractionating and preserving an expiring bag of whole blood might extend the life of those red cells. They obtained 21- day old (expiring) whole blood and separated the red cells, preserving them using the usual technique. They then analyzed the cells weekly until expiration at 42 days for viability, storage damage and coagulation status.

Here are the factoids:

  • The number of units tested was not listed in the abstract
  • Damage from storage of the extracted red cells appeared to be consistent with normal damage expected from packed red blood cells
  • When mixed with plasma with a 1:1 ratio, clotting time, clot formation time, and maximum clot formation did not change as the salvaged cells aged

The authors concluded that the salvaged cells aged just like packed RBCs. They suggested that this may provide a method for extending the life of whole blood and allowing transfusion into patient in hemorrhagic shock.

My comment: This is an intriguing paper and suggests a way of extending the life and use of valuable whole blood. It appears to have been well done and analyzes standard markers of red cell dysfunction. However, the authors did not provide the number of units they tested. This is critical, since they are trying to show that the values tested are statistically the same (no difference between packed RBCs and those salvaged from whole blood). Some of their comparison numbers appear very different, but are not statistically significant. I worry that the number of units tested might be too small to show a difference.

Here is my question for the authors and presenter:

  1. Exactly how many units of whole blood did you use in this study? And did you do a power analysis to ensure that you don’t have a Type II error (false negative) with the “not significant” results?

This is a great idea and stands to save money and stretch our supply of blood!

Reference: Save it – don’t waste it! Maximizing utilization of erythrocytes from previously stored whole blood. EAST Annual Assembly abstract #6, 2020.

Best Of EAST #4: Cannabis And Venous Thromboembolism

Cannabis and cannabidiol (CBD) are all over the news these days. CBD is legal everywhere, and it seems that more states are legalizing cannabis every few months. There are a few hints in PubMed that cannabinoids (THC) may have some impact on clotting, possibly causing hypercoagulability.

The group at the University of Arizona in Tucson decided to look into this in trauma patients. They did a two year scan of the TQIP database and stratified patients based on their THC status. They matched up THC positive and negative patients and examined thromboembolic events (deep venous thrombosis, pulmonary embolism, stroke, MI) and mortality.

Here are the factoids:

  • Nearly 600,000 patients records were in the database pull, but only 226 patients were THC+
  • They were matched at a 1:2 ratio with similar THC – patients (452)
  • No differences were found in the usual demographics, injury severity, use of DVT prophylaxis, and hospital length of stay
  • The THC+ group had a significantly higher incidence of overal thromboembolic complications (9% vs 3%)
  • Both DVT ( 7% vs 2%) and PE (2.2% vs 0.2%) were significantly higher in the THC+ group
  • No differences were seen in strokes or MI

The authors concluded that THC increases the risk of DVT and PE and that early identification and treatment for thromboembolic complications is required to improve outcomes in this high risk subset of trauma patients.

My comment: Seems compelling, right? But this is one of those abstracts that you have to read really closely. You have two groups of patients that are being compared, and a few statistical differences were found. The groups are small, but even so these differences are great enough to reach statistical significance. Great!

But, now step back and look carefully at the larger patient group. There are almost 600,000 patients there, but am I to believe that only 226 patients (0.04%) were using cannabis? According to recent statistics, approximately 8% of the US population currently uses marijuana. So in theory, about 47,500 patients in the TQIP sample should have tested positive. For whatever reason, this data point was not collected. Could data from the other 47,274 have changed the study result? Probably. 

Here are my questions for the authors and presenter:

  1. What was the impetus for this study? I was not aware of clotting issues due to THC and there is little in the published literature. I’d love to hear some history and be able to read more about this.
  2. What about the long time interval that a patient will test THC+ after partaking? THC remains in body fat for a month or more, and the qualitative test commonly used will provide a positive for weeks after the last use. How long do the thrombogenic effects of THC last? The THC+ result recorded in the dataset could be from THC use well before the traumatic event.
  3. How do you think your small sample of THC+ patients impacts your results given the much larger number of expected marijuana users in the sample?

This is intriguing work. Let’s here more!

Reference: Impact of marijuana on venous thromboembolic events: cannabinoids cause clots in trauma patients. EAST Annual Assembly abstract #4, 2020.