Chest pain observation units run by the Emergency Department are fairly popular – and it’s easy to see why. It eliminates the need to fight a hospitalist for admission, allows for complete coverage of medicolegal liability, captures another set of billing codes for ED revenue, and keeps the cardiologists happy with a steady stream of interpretation and consultation revenue.
Duke University has one of these such chest pain observation units, and this study is a retrospective evaluation of the subgroup of patients aged less than 40 years. Of the 2,231 patients observed for suspected acute coronary syndrome, 362 met eligibility based on age. Of these 362 patients, median age 36, 238 underwent stress testing and the remainder underwent serial enzymes.
From this cohort, there was a single true positive – defined as a patient who underwent a coronary angiogram with an intervention performed.
There were, however, 14 false positives – indeterminate or positive stress tests and one set of positive biomarkers, leading to five negative invasive coronary angiograms.
The authors sum it up quite nicely: “The extremely risk- adverse physician cannot totally exclude the possibility of ACS based on age, but it seems that routine observation for such patients may cause the potential for as much harm as good.”
“Utility of Observation Units For Young Emergency Department Chest Pain Patients”
www.ncbi.nlm.nih.gov/pubmed/22975283
Month: March 2013
“ePlacebo”-Controlled Trials?
This is a bit of a fascinating application of clinical informatics – using retrospective patient cohorts and propensity matching techniques to reduce the need for placebo groups in future trials.
This is work done by Pfizer on their own internal database, to address the ethical and financial concerns regarding recruiting large populations for new clinical trials. For example, if you’re testing a new diabetes medication – do you really need a new control group, or can you sort of re-use the control group you had from the previous trial? The answer of course, has traditionally been no – but their answer is yes-and-no. Using their database of over 24,000 trials, they were able to identify 4,075 placebo-controlled groups, with varying degrees of data integrity, crossover, and parallel status. They then suggest these groups could be used, when appropriate, as comparators in future studies in the same domain.
This is certainly an interesting application of clinical informatics – creating temporal databases of clinical trial patients with the potential to augment the evaluation of new medications. What’s nice is that these authors appropriately recognize the limitations of such a database, noting it may only supplement, not replace placebo arms in future trials.
“Creation and implementation of a historical controls database from randomized clinical trials”
www.ncbi.nlm.nih.gov/pubmed/23449762
Stroke or Stroke Mimic? Who Cares!
Suppose you’re “lucky” enough to be taken to an experienced stroke center if you have stroke-like symptoms. After all, they see strokes every day, are experts in the diagnosis of stroke, and have given thousands of patients thrombolytics. However, how often might they be wrong, you ask?
Oh, they estimate about 1 in every 50. But, truthfully, it’s probably much worse.
This is a multi-center observational cohort that purports to identify the percentage of patients treated with tPA and subsequently diagnosed with stroke mimics. Out of the 5518 patients in their cohort, 100 were identified as stroke mimics. Two of the 100 had sICH by NINDS criteria, but none died. Therefore, these authors confirm, tPA is safe even when they’re wrong, and the collateral damage of racing to tPA is low.
Of course, their methodology for identifying a stroke mimic is hugely skewed towards maintaining the diagnosis of ischemic stroke. Only patients in whom clinical details did not suggest a vascular etiology or a clear alternative diagnosis were labeled mimics. Patients with nonspecific features, non-contradictory imaging, or lacking definite evidence favoring stroke mimic remained as diagnoses of acute stroke.
So, even at experienced stroke research institutions – 1 in 50 with the most generous of criteria. What’s the chance real-world performance approaches anything close to this level of diagnostic skill?
The authors, of course, declare multiple financial conflicts of interest with the manufacturer of tPA.
“Safety of Thrombolysis in Stroke Mimics : Results From a Multicenter Cohort Study”
www.ncbi.nlm.nih.gov/pubmed/23444310
Does Size Matter? (Chest Tube Size)
That is, apparently, the question being asked by the trauma folks at Los Angeles County Hospital. Traditionally, traumatic pneumothorax with accompanying hemothorax is routinely treated by the largest chest tube possible. Theoretically, smaller chest tubes will clog with debris or blood clot, requiring additional thoracostomy tubes or interventions.
However, these authors note several simulations of chest tube drainage indicating tubes as small as 14 French may be adequate. They also hypothesize these larger chest tubes are as painful as tragically possible, and the tradition of large chest tubes results in undue suffering.
The answer…remains unsettled. There was no difference observed in their analysis of chest tubes of maximum size versus smaller-than-maxiumum size. But, a 28-32 Fr chest tube is still a pretty darn large tube. I’m not surprised that pain and drainage characteristics were not different. If they really wanted to push the envelope, they ought to look at the truly small tubes – at least, if their goal is clinically relevant pain reduction.
“Does size matter? A prospective analysis of 28–32 versus 36–40 French chest tube size in trauma”
www.ncbi.nlm.nih.gov/pubmed/22327984
The NICE Traffic Light Fails
Teasing out serious infection in children – while minimizing testing and unnecessary interventions – remains a challenge. To this end, the National Institute for Health and Clinical Excellence in the United Kingdom created a “Traffic Light” clinical assessment tool. This tool, which uses colour, activity, respiratory, hydration, and other features to give a low-, intermediate-, or high-risk assessment.
These authors attempted to validate the tool by retrospectively applying it to a prospective registry of over 15,000 febrile children aged less than 5 years. The primary outcome was correctly classifying a serious bacterial infection as intermediate- or high-risk. And the answer: 85.8% sensitivity and 28.5% specificity. Meh.
108 of the 157 missed cases of SBI were urinary tract infections – for which the authors suggest perhaps urinalysis could be added to the NICE traffic light. This would increase sensitivity to 92.1%, but drop specificity to 22.3% – if you agree with the blanket categorization of UTI as SBI.
Regardless, the AUC for SBI was 0.64 without the UA and 0.61 with the UA – not good at all.
“Accuracy of the “traffic light” clinical decision rule for serious bacterial infections in young children with fever: a retrospective cohort study”
www.ncbi.nlm.nih.gov/pubmed/23407730