Category Archives: Complications

Why Do Trauma Patients Get Readmitted?

Readmission of any patient to the hospital is considered a quality indicator. Was the patient discharged too soon for some reason? Were there any missed or undertreated injuries? Information from the Medicare system in the US (remember, this represents an older age group than the usual trauma patient) indicates that 18% of patients are readmitted and 13% of these are potentially preventable.

A non-academic Level II trauma center in Indiana retrospectively reviewed their admissions and readmissions over a 3 year period and excluded patients who were readmitted on a planned basis (surgery), with a new injury, and those who died. This left about 5,000 patients for review. Of those, 98 were identified as unexpected readmissions. 

There were 6 major causes for readmission:

  • Wound (23) – cellulitis, abscess, thrombophlebitis. Two thirds required surgery, and 4 required amputation. All of these amputations were lower extremity procedures in obese or morbidly obese patients.
  • Abdominal (16) – ileus, missed injury, abscess. Five required a non-invasive procedure (mainly endoscopy). Only 2 required OR, and both were splenectomy for spleen infarction after angioembolization.
  • Pulmonary (7) – pneumonia, empyema, pneumothorax, effusion. Two patients required an invasive procedure (decortication, tube placement).
  • Thromboembolic (4) – DVT and PE.  Two patients were admitted with DVT, 2 with PE, and 1 needed surgery for a bleed due to anticoagulation.
  • CNS (21) –  mental status or peripheral neuro exam change. Eight had subdural hematomas that required drainage; 3 had spine fractures that failed nonoperative management.
  • Hematoma (5) – enlargement of a pre-existing hematoma. Two required surgical drainage.

About 14% of readmissions were considered to be non-preventable by a single senior surgeon. Wound complications had the highest preventability and CNS changes the lowest. Half occurred prior to the first followup visit, which was typically scheduled 2-3 weeks after discharge. This prompted the authors to change their routine followup to 7 days.

Bottom line: This retrospective study suffers from the usual weaknesses. However, it is an interesting glimpse into a practice with fewer than the usual number patients lost to followup. The readmission rate was 2%, which is pretty good. One in 7 were considered “preventable.” Wounds and pulmonary problems were the biggest contributors. I recommend that wound and pulmonary status be thoroughly assessed prior to discharge to bring this number down further. Personally, I would not change the routine followup date to 1 week, because most patients have far more complaints that are of little clinical importance than compared to 2 weeks after discharge.

Reference: Readmission of trauma patients in a nonacademic Level II trauma center. J Trauma 72(2):531-536, 2012.

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Fatigue V: Your Patients

I’ve spent the past several posts detailing how interrupted sleep interferes with the health and effectiveness of trauma professionals. But what about our patients? Being in the hospital is nothing like trying to sleep at home. The beds are terrible. There is noise in the hall. Their roommate is confused and calls out at all hours. Nurses keep coming in to check vital signs. The pulse oximeter beeps every 10 minutes.

How bad is it, really? There is no trauma patient-specific literature yet on the topic. But there is a recently published paper detailing the experience of general surgery patients admitted after elective procedures that is very revealing. The group at Dartmouth-Hitchcock Medical Center recruited adults who stayed at least one night at the hospital.

Prior to surgery, each patient completed a questionnaire that measured their baseline home sleep quality. Postop, they completed another questionnaire designed to measure their in-hospital sleep quality.  Each patient was fitted with a Fitbit Inspire HR tracker, which they wore during their entire hospitalization.  After discharge home, they completed a final outpatient sleep questionnaire.

Here are the factoids:

  • A total of 74 patients were recruited and 54 completed all phases of the study; 59 finished all of the pre-discharge phases
  • The average inpatient sleep score was 49/100, where scores less than 50 are considered substandard
  • The major culprit for in-hospital sleep disturbance was nighttime awakenings
  • Patients who had better home sleep quality tended to have a higher in-hospital score (65)
  • Sleep quality was so poor that only 40% of Fitbit devices were able to record sleep time on the first postop night, and that average time asleep was 4.7 hours
  • As expected, patients with a roommate did not sleep as well as those in private rooms
  • Average sleep time increased over subsequent nights to about 6 hours, which is still short of the recommended 7 hour minimum
  • About 88% of patients were poor sleepers preop (!), and this did not change after they returned home (85%)

Bottom line: Sleep quality in the hospital is terrible! I can vouch for this from the standpoint of being a surgeon on call, and also from one experience as a patient. There is very good data on the adverse effects of sleep loss. Fasting glucose and systolic blood pressure rise significantly after a single night of poor sleep. When these occur in a hospital, this sets the clinicians into a frenzy of prescribing sliding scale insulin or antihypertensives and other meds that are probably not needed.

There are numerous other more subtle effects as well. The best way to avoid them is to promote good sleep. But how can you do this in the hospital? Here are some tips:

  • Be aware that the way you order medications (tid vs q8hrs) has a big impact on when the evening/night doses are given. Talk to your pharmacist so your patient only gets meds when they would normally be awake and not in the middle of the night.
  • Remove unnecessary monitors that might alarm during sleep. Pulse oximeters are probably the biggest culprit. Does it need to be continuous, or can (very) occasional spot checks be done?
  • Does your patient really need vital signs taken during the middle of the night? After the first few shifts, most ward patients do not.
  • Watch out for the phlebotomists! They love to circulate early so lab results are available at the crack of dawn. Can’t it wait?
  • Some practice guidelines call for repeat scans or other studies after a certain number of hours. If one is due at 3am, can’t it wait until morning? Really?
  • On a daily basis, review all actual or potential nighttime interruptions with the patient and their nurse. Discontinue or reschedule anything that really can’t wait until morning.

Failing to provide for good sleep quality sets your patient up for complications, abnormal vitals and blood tests, and altered mental status. Do everything you can to optimize their sleep!

Reference: Deep sleep and beeps: sleep quality improvement project in general surgery patients. JACS 232(6):882-888, 2021.

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How Quickly Does Hemoglobin Drop After Acute Bleeding?

We all know that hemoglobin / hematocrit drop after blood loss. We can see it decreasing over the days after acute bleeding or a major operative procedure (think orthopedics). And we’ve been told that the hemoglobin value doesn’t drop immediately after acute blood loss.

But is it true? Or is it just dogma?

A reader sent me a request for some hard references to support this. When I read it, I knew I just had to dig into it. This is one of those topics that gets preached as dogma, and I’ve bought into it as well.

Now, I have personally observed both situations. Long ago, I had a patient with a spleen injury who was being monitored in the ICU with frequent vital signs and serial blood draws (but I don’t do that one anymore). He was doing well, then became acutely hypotensive. As he was being whisked off to the OR, his most recent hemoglobin came back at 10, which was little changed from his initial 11.5 and certainly no independent reason to worry.

But hypotension is a hard fail for nonoperative solid organ management. In the OR, anesthesia drew another Hgb at the end of the case, and the value came back 6.

Similarly, we’ve all taken care of patients who have had their pelvis fixed and watched their Hgb levels drop for days. Is this anecdotal or is it real? The doctor / nursing / EMS textbooks usually devote about one sentence to it, but there are no supporting references.

I was only able to locate a few older papers on this. The first looked at the effect of removing two units of red cells acutely. Unfortunately, the authors muddied the waters a little. They were only interested in the effect of the lost red cell mass on cardiac function, so they gave the plasma back. This kind of defeats the purpose, but it was possible to see what happened to Hgb levels over time.

Here were there findings over time for a group of 8 healthy men:

Time Hbg level
Before phlebotomy 14.4
1 week after 11.7
4 weeks after 12.6
8 weeks after 13.6
16 weeks after 13.9

So the nadir Hgb value occurred some time during the first week after the draw and took quite some time to build back up from bone marrow activity.

That’s the longer term picture for hemoglobin decrease and return to normal. What about more acutely? For this, I found a paper from a group in Beijing who was trying to measure the impact of Hgb loss from a 400cc blood donation on EEG patterns. Interesting.

But they did do pre- and post-donation hemoglobin values. They found that the average Hgb decreased from 14.0 to 13.5 g/dl during the study, which appeared to be brief. Unfortunately, this was the best I could find and it was not that helpful.

Bottom line: Your patient has lost whole blood. So, in theory, there should be no Hgb concentration difference at all. But our bodies are smart. The kidneys immediately sense the acute hypovolemia and begin retaining water. The causes ongoing hemodilution within seconds to minutes. Additionally, fluid in the interstitial space begins to move into the vascular space to replace the volume lost. And over a longer period of time, if no additional fluid is given the intracellular water will move out to the interstitium and into the vascular space.

But these things take time. There is an accelerating curve of hemodilution that takes place over hours. The slope of that curve depends on how much blood is lost. A typical 500cc blood transfusion will cause a 0.5 gm/dl drop over several minutes to an hour. We don’t have great data on the exact time to nadir, but my clinical observations support a hyperbolic curve that reaches the lowest Hgb level after about 3 days.

Unlike this curve, it levels off and slowly starts to rise after day 3-4 due to bone marrow activity.

The steepness of the curve depends on the magnitude of the blood loss. After a one unit donation, you may see a 0.5 gm/dl drop acutely, and a nadir of 1 gm/dl. In the case of the acutely bleeding patient with the spleen injury, the initial drop was 1.5 gm/dl. But two hours later it had dropped by over 5 gm/dl. 

Unfortunately, the supporting papers are weak because apparently no one was interesting in proving or disproving this. They were more interested in cardiac function or brain waves. But it does happen. 

Here’s the takeaway rule:

In a patient with acute bleeding, the initial hemoglobin drop is just the tip of the iceberg. Assume that this is only a third (or less) of how low it is going to go. If it has fallen outside of the “normal” range, call for blood. You’ll need it!

References:

  1. Effect on cardiovascular function and iron metabolism of the acute removal of 2 units of red cells. Transfusion 34(7):573-577, 1994.
  2. The Impact of a Regular Blood Donation on the Hematology
    and EEG of Healthy Young Male Blood Donors. Brain Topography 25:116-123, 2012.

 

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Routine Duplex Screening For Venous Thromboembolism

Venous thromboembolism (VTE) is a potential problem for all hospitalized patients, and traumatic injury is yet an additional risk factor for its occurrence. Most trauma centers have some kind of risk assessment tool to help the tailor their chemoprophylaxis regimen to patients most at risk. But far fewer have adopted the use of screening ultrasounds to monitor for new onset VTE that would dictate conversion to therapeutic treatment.

Unfortunately, in the US, the Centers for Medicare and Medicaid Services (CMS) has deemed VTE as a “never” event and penalizes hospitals when they report it. One of the unintentional consequences of this (or is it?) is that hospitals may then pressure trauma programs to avoid surveillance in order to “make the numbers look better.” Remember Law X from Samuel Shem’s House of God?

X. If you don’t take a temperature, you can’t find a fever.

Similarly, if you don’t do a duplex screen, you probably won’t detect VTE. Now granted. some patients develop classic symptoms like edema, pain, and tenderness. But not that many.

But is this wise? My contention has been that if the patient doesn’t develop symptoms that catch your attention, yet they develop VTE that you don’t know about, they are at risk for more serious complications like pulmonary embolism (PE). And you are blithely unaware.

The trauma group at Intermountain Medical Center in Salt Lake City performed an elegant study to determine the impact of screening for VTE in their trauma patients. They performed a prospective, randomized trial on trauma patients admitted over a 30-month period. Patients were included if they were judged to be at moderate to high risk based on their risk assessment profile (RAP) score. Patients were excluded if they were children, had VTE or PE within 6 months prior to hospitalization, or had some type of hypercoagulable state.

Patients were sequentially randomized to no duplex screening vs screening on days 1, 3, 7, and then weekly thereafter. The primary outcome measure was PE during the hospital stay. Secondary outcomes consisted of a number of factors relating to development of DVT.

Here are the factoids:

  • Nearly two thousand patients were enrolled, with about 995 patients in each group and no differences in demographics
  • The ultrasound group had significantly more below-knee (124 vs 8) and above knee (19 vs 8) DVT identified (no surprise there)
  • The ultrasound group had significantly fewer pulmonary emboli than the no ultrasound group (1 vs 9) (lots of surprise here!)
  • Mortality was similar during the hospital stay and for 90 days after

Bottom line: If you look for it, you will find it! This is the definition of surveillance bias. But in in this study, looking for clots in the legs may also decrease the number of patients who develop symptomatic pulmonary embolism. How could this be?

There are a few possibilities. The majority of DVT found in the surveillance group were located distally. Although there is some uncertainty as to how likely these are to embolize, it is probably very low. So let’s ignore them for now and assume that only the proximal clots might embolize.

This leaves an extra 11 DVT found in the surveillance group over and above the no-ultrasound group. Despite that, the surveillance group had only one PE vs 9 in the no-ultrasound group!

Another explanation was that the ultrasound guided changes in management, shifting to management to therapeutic drug dosing. The authors did not find a significant difference between the use of therapeutic vs prophylactic dosing between the groups. But there was a difference. Although the overall study was well-powered, there really weren’t enough numbers to show whether there was a true difference in therapeutic dosing. Fourteen patients in the ultrasound group got therapeutic anticoagulation compared to only 4 in the no-surveillance group. I think this is the actual reason.

Overall, this is a well-designed and well-executed study that shows why taking the Ron Popeil approach to DVT prophylaxis (“set it and forget it”) doesn’t work. Patients do occasionally develop proximal DVT on standard chemoprophylaxis (and frequently develop distal DVT), but it doesn’t always result in obvious signs and symptoms. This study shows that if you don’t look for it, you may not know until they suddenly develop chest pain, air hunger, and worse! So consider carefully if your practice guideline doesn’t yet include surveillance.

Reference: Trauma Patients at Risk for Venous Thromboembolism who Undergo Routine Duplex Ultrasound Screening Experience Fewer Pulmonary Emboli: A Prospective Randomized Trial. J Trauma, publish ahead of print, Publish Ahead of Print. DOI: 10.1097/TA.0000000000003104, February 4, 2021.

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Best of EAST #2: Blood Transfusion And Nosocomial Infection

This abstract falls into the “interesting, but how can we use this bit of information” category. We’ve known that transfusing packed red cells raises nosocomial infection rates for at least 15 years. The group led by MetroHealth in Cleveland combined forces with the Vanderbilt trauma group to re-look at their data from the PAMPer trial with respect to trauma patients.

The PAMPer trial (Prehospital Air Medical Plasma) examined the effect of tranfusion of two units of plasma in the air ambulance on mortality, transfusion need, and complications. Half of the patients got plasma plus standard care, and the other half standard care alone.

This abstract uses PAMPer trial data to examine the impact of giving any amount of blood on nosocomial infection in these patients. These infections included pneumonia, bloodstream infection, C Diff colitis, empyema, and complex intra-abdominal infection.

The group retrospectively analyzed the prospectively collected PAMPer data and used logistic regression models to test for an association.

Here are the factoids:

  • A total of 399 patients with the usual trauma demographics were included (younger male, moderately injured, blunt mechanism)
  • Ten percent of patients died, and 23% developed nosocomial infections
  • Pneumonia was by far the most common complication (n=67) with all others in the low teens or below
  • Although only two thirds of patients received plasma, 80% were given PRBCs and 27% received platelets
  • Patients who received any amount of packed cells had a 2.3x increase in nosocomial infections, and the number given increased the rate of nosocomial infection (1.06x)

The authors concluded that patients in the PAMPer trial who received at least one unit of blood “incurred a two-fold increased risk of nosocomial infection” and that this risk was dose dependent.

My analysis: The biggest obstacle for me to buy into this work is the enrolled patient group. Studies in which you borrow someone else’s data are always a bit problematic. You have no control over the variables, as they’ve been determined by someone else.

In this case, the dataset could only be controlled for age, sex, and ISS. But what about all the other stuff that might have an impact on infections? Things like pulmonary injury, the 20% of patients who had penetrating injury, and severe TBI patients with their propensity to develop VAP.

The odds ratios of the associations were a bit on the low side. Sure, the overall nosocomial infection odds ratio was 2.37 but the confidence interval was 1.14 to 4.94. This is very wide and it means that the odds could have been anywhere from 1.14x to almost 5x. This suggests that the study group may not have been large enough to give us a clear picture. And the odds ratio for number of PRBC units vs infection was only 1.06 with a tighter confidence interval. So even if it is present, this association is very, very weak. I like to see ridiculously large odds ratios when reviewing observational studies like this where the input data is constrained.

My final comment on this study deals with its utility. These are trauma patients. They are bleeding. We’ve known that transfusions may increase the nosocomial infection rate in critically ill patients for at least 15 years. But we will still have to give the patients blood. So what are we to do?

Here are some questions for the authors and presenter:

  • Please comment on the limitations you faced using the PAMPer dataset. Were you satisfied with the range of variables available? Which additional ones would you have liked to work with?
  • Do you feel that the 399 patients provided enough statistical power for analysis? The confidence intervals are large and very close to the OR=1 line.
  • What should we do with your conclusions? Can we translate this into clinical practice?

One final note: the patients did not “incur increased risk.” Rather, there was an association with increased risk of infection. We really don’t know if it was from the blood or something else that was not recorded in the PAMPer dataset.

Reference: Dose-dependent association between blood transfusion and nosocomial infections in trauma patients: a secondary analysis of patients from the PAMPer trial. EAST 2021, Paper 3.

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