The Fixed-Ratio Massive Transfusion Answer

After years of wondering and wandering, we finally have the definitive answer for how best to resuscitate the severely-injured trauma patient – transfusion ratios best mimicking whole blood.  You know, just as we all expected, just as these authors hoped, and just what’s been reported from prior observational series and military combat experience.

More or less.

Regardless, this study – the Pragmatic, Randomized, Optimal Platelet and Plasma Ratios (PROPPR) trial – was a remarkable undertaking in logistics.  Each participating Level 1 trauma center incorporated sealed coolers into their ready blood supply, providing a random allocation of product ratio when the massive transfusion protocol was activated.  As transfusion continued, more coolers with the same ratio arrived.  As best as can be implemented, this reduces the immortality bias seen in other observational series – where survivors were survivors in part, basically, because they survived.

This trial randomized patients to 1:1:1 vs. 1:1:2 – that is, equal numbers of FFP, platelets and RBCs, or half as much FFP and platelets as RBCs.  Ultimately, it didn’t precisely test those same ratios, except as the initial resuscitation strategy.  Following the intervention period, the 1:1:2 arm caught up a bit with plasma and FFP – but the quantities transfused were not substantial.

Technically, this is a negative trial – the mortality advantage favoring the 1:1:1 cohort did not reach statistical significance at 24 hours or 30 days.  However, the authors powered the study expecting a 10% mortality advantage – and instead it was only 4.2% (95% CI -1.1 to 9.6) and 3.7% (95% CI -2.7 to 10.2) at each time point, respectively.  We are then left with the question whether this small difference reflects the underlying truth or chance.

Do the secondary aspects of these data validate the difference?  The expected advantage of 1:1:1 resuscitation is the warding off of evil spirits associated with transfusion-related coagulopathy – and we see in this study the primary driver of differences in mortality was related to deaths secondary to exsanguination.  Likewise, a greater number in the 1:1:1 group achieved satisfactory hemostasis.  So, using a Bayesian approach to interpreting the statistical tests for mortality, it is reasonable to adopt approaches based initial 1:1:1 resuscitation when massive transfusion is necessary, despite the limitations of the evidence.

One oddity worth noting in these data were the relatively small differences in sepsis and ARDS in the 1:1:1 group.  Increased use of FFP and, in particular, platelets are associated with these transfusion-related complications – and it has always been of particular interest whether a 1:1:1 ratio is safe, for precisely these reasons.  The inclusion of platelets in the 1:1:1 randomization may also be a matter for debate; few patients had any indication for platelets following the intervention, and further work could consider the relative utility of aggressive use of platelets.

Overall, however, this is best evidence to date the 1:1:1 ratio is a worthy initial target.

“Transfusion of Plasma, Platelets, and Red Blood Cells in a 1:1:1 vs a 1:1:2 Ratio and Mortality in Patients With Severe Trauma”
http://www.ncbi.nlm.nih.gov/pubmed/25647203

Which Review of Tamiflu Data Do You Believe?

Ever since its introduction, there have been skeptics regarding the utility of oseltamivir and other neuraminidase inhibitors for the treatment of influenza.  Roche has profited tremendously off strategic stockpiling by many governments as a response to pandemic influenza – yet, nearly all the data comes from Roche-conducted trials, and the data has been persistently cloaked from independent review.  This past year, after much strife and public shaming, the Cochrane Collaboration received some access to clinical trial reports to conduct an independent review.  This review found, on average, adults receiving early treatment with oseltamivir benefited by reduction in symptom duration from 7 days to 6.3 days.  No benefit was found for reduction in respiratory infectious complications or hospitalization, the truly critical need during influenza outbreaks.

However, a second group also conducted an independent review – the “Multiparty Group for Advice on Science”.  Their results, based on an individual-patient meta-analysis, are published in the Lancet and offer similar – yet wildly different – conclusions.  They find, as did the Cochrane group, approximately a 17-hour reduction in symptoms in the intention-to-treat population across the eight Roche trials evaluated.

Similar to the Cochrane review, they perform secondary analyses for “lower respiratory tract infection”(e.g., bronchitis or pneumonia) and hospitalization, stratified by ITT and ITT-infected populations.  Most prominently emphasized are the results for the ITT-infected population, in which the antibiotics for LRTI were provided to 4.2% in the oseltamivir cohort, compared with 8.7% in placebo.  Likewise, 0.9% of patients were hospitalized for any cause compared with 1.7% of placebo.  The authors therefore conclude oseltamivir use decreased infectious complications of influenza.

These numbers, however, are entirely different from the Cochrane review.  The Cochrane review found a 1.4% hospital admission rate in the oseltamivir cohort and 1.8% in the placebo cohort.  Broken down by trial, the admit rates for the oseltamivir cohort in the MUGAS analysis compared with the Cochrane review:

  • M76001: 7/965 vs. 9/965
  • WV15670: 1/241 vs. 1/484
  • WV15671: 1/210 vs. 6/411
  • WV15707: 2/17 vs. 2/17
  • WV15812+: 6/199 vs. 9/199
  • WV15819+: 6/360 vs. 9/362
  • WV16277: 2/226 vs. 2/225

The differences in WV15670 and WV15671 appear to stem, at least in part, due to the MUGAS analysis being restricted to only trial patients taking 75mg twice daily, and not 150mg twice daily.  However, it is otherwise entirely unclear how the Cochrane group found extra hospitalizations in the other trials the MUGAS group did not – particularly considering the hospitalization numbers in the placebo cohorts were essentially identical.  Might it be partly a result of the MUGAS group receiving their data directly from a Roche web portal, while the Cochrane group reviewed the individual clinical study reports?

Rather, might it be revealing to pry into the genesis of the “Multiparty Group for Advice on Science”?  Is it an unbiased, independent clearinghouse for re-analysis of trial data?  Do they have a long track record of respected publications in multiple disciplines?  Unfortunately, neither of these conjectures are true – making it increasingly likely they are a puppet foundation fraught with conflict-of-interest.  MUGAS and the present work were funded by an unrestricted grant from Roche.  Furthermore, MUGAS, along with the European Scientific Working group on Influenza (ESWI), are projects of Semiotics, a scientific branding and communication company specializing in influenza.  The stated goal of Semiotics is promoting corporate science and ensuring its place on top of the policy agenda – and MUGAS is one of their “brands”.  This ought to very clearly demonstrate MUGAS is not a scientific enterprise, and rather an organization tasked with the sort of advocacy as best represents the needs of its sponsors.

Any bias might also be clear just in the style used to present results.  These authors present the tiny absolute differences in hospitalization and infectious complications in forest plot figures using only relative risk, rather than absolute risk.  This serves to inflate the apparent effect size.  Conversely, they present the increased incidence of adverse effects in a table culminating in adjusted absolute risk, with the opposite effect.  This manner of presentation persists in their Discussion, highlighting a “significant 63% reduction in risk of hospitalization”, compared with “absolute increases of 3.7% for nausea and 4.7% for vomiting.”

So – the results of an analysis performed by a “brand”, highlighting results discordant with a prior unbiased analysis.  Where is the peer review vetting such discrepancies?  With so many professional reputations and so much revenue at stake – which report do you believe?

“Oseltamivir treatment for influenza in adults: a meta-analysis of randomised controlled trials”
http://www.thelancet.com/journals/lancet/article/PIIS0140-6736(14)62449-1/abstract

Additional editorial content:
“The BMJ Today: The FDA and CDC’s disagreement over Tamiflu, and the spy who isn’t”
http://blogs.bmj.com/bmj/2015/02/05/the-bmj-today-the-fda-and-cdcs-disagreement-over-tamiflu-and-the-spy-who-isnt/

The Incredible Power of Drug Cost on Treatment Response

Everyone is familiar with the placebo and nocebo effects – when the expectation of benefit or harm produces positive or negative effects, respectively.  Impressively, however, the power of such effects can be modulated on another level by incorporating cost into the placebo effect.

This fascinating little study tested the effect of two different placebo medications on motor and brain activation in patients suffering from Parkinson’s disease.  Initially, each patient received motor and fMRI testing before and after levodopa administration.  Then, on a subsequent visit, patients received subcutaneous injections of saline 4 hours apart – with participants being told each was the same novel dopamine antagonist, one of which was manufactured using a “cheap” manufacturing process and one using an “expensive” process.  Each participant again received motor and fMRI testing following each injection.

As somewhat expected, each placebo injection produced some improvement in motor function – with the effect reaching statistical significance and almost 30% improvement from baseline for the “expensive” placebo.  Even more impressive, the “expensive” placebo was not too far off the effects of levodopa, which produced approximately a 50% improvement in motor symptoms from baseline.  Most entertainingly, however, the placebo effects were even present on fMRI imaging.  The “expensive” placebo showed brain activation levels similar to levodopa, while the “cheap” placebo had a differing distribution of activity apparently consistent with increased effort.

Yet again, the very real power of placebo – with its magnitude of effect tied to expectations related to cost!

“Placebo effect of medication cost in Parkinson disease”
http://www.ncbi.nlm.nih.gov/pubmed/25632091

Inside a Neurologist’s Mind: tPA For Everyone!

We all have our anecdotal stories from academic medical centers staffed by stroke neurologists, cases in which they have called for thrombolytic therapy in acute ischemic stroke for profoundly inappropriate candidates.  Hearing such sad tales, one hopes such rogue uses of lytics are the lunatic fringe, isolated cases of madness and zealotry.

But, no.

This survey of general and vascular neurologists at two academic institutions in New York demonstrates such aggressive use of tPA for stroke is the pervasive norm, rather than an isolated occurrence.  These authors provided 40 clinicians with a survey consisting of 110 case scenarios of patients presenting with symptoms of acute stroke.  These case scenarios were further stratified by NIHSS, with 22 cases each of NIHSS 1 through 5.  Of the 17 clinicians responding, it was almost unanimous they would use tPA for all cases of NIHSS 3, 4, and 5.  Neurologists would use lytics 57% of the time at NIHSS 2, and 37% of the time with NIHSS 1.

Now, the NIHSS is non-linear, and significant disability can be present at NIHSS 1 and 2 – but even remotely considering lysis at NIHSS 1 or 2 should be the exception rather than an almost balanced split.  In a world where the new ACEP Clinical Policy draft is rolling back its level of recommendation for tPA, it is simply boggling to see how the other half thinks – that no frontier is too formidable for tPA.

“To Treat or Not to Treat?  Pilot Survey for Minor and Rapidly Improving Stroke”
http://www.ncbi.nlm.nih.gov/pubmed/25604250

More Tests, Longer Turnaround, Longer LOS

In this Friday’s edition of “It’s Science!”, we cover this recent publication demonstrating, essentially, what we already knew:  throughput suffers when test turnaround times are longer!

To do so, however, requires (apparently) cross-classified random-effect modeling, linking Emergency Department information systems to laboratory test data.  These authors evaluated a retrospective, multi-site cohort consisting of 27,656 linked ED and laboratory encounters and modeled the attributable effect of test turnaround time on ED length-of-stay.  They discovered, rather obviously, patients receiving more tests had longer ED LOS.  Working backwards, furthermore, they found for every 30 minute increase in laboratory test turnaround time, there was an approximately 17 minute increase in median ED length-of-stay.  It’s not a 1:1 relationship – as you can imagine situations where the ED LOS is dictated rather by radiography, procedures, or consultations, rather than laboratory testing – but increases in a relatively linear fashion.

So, depending on the structure and flow of your Emergency Department, there may be substantial benefits to focusing on improved laboratory turnaround times.  And, likewise, you can probably improve all your times by simply ordering fewer tests!

“The Effect of Laboratory Testing on Emergency Department Length of Stay: A Multihospital Longitudinal Study Applying a Cross-classified Random-effect Modeling Approach”
http://www.ncbi.nlm.nih.gov/pubmed/25565488

Ceftriaxone: It’s Not For Stroke

Negative trials are just as important – if not moreso – than positive trials.  Without negative trials, well-meaning clinicians continue with unproven and unverified treatments, incurring unnecessary costs and exposing patients to unneeded potential adverse effects.

This prospective trial of 2,550 patients randomized patients post-stroke to four days of prophylactic ceftriaxone versus no treatment, using an open-label, masked endpoint design.  The theory – some of the mortality and disability post-stroke may be in excess as result of infectious (primarily respiratory) complications.  The fact – no.  There was no difference in functional outcome at any modified Rankin Score ordinal cut-off, nor mortality.  There were actually not fewer cases of pneumonia in the ceftriaxone group, but urinary tract infections were significantly suppressed.  Clostridium difficile infection occurred only in two cases, both in the ceftriaxone group.

As a random aside, the median NIHSS in this trial was 5 – and 37% of patients achieved mRS 0-1.  This is rather surprisingly low, considering the SITS-MOST cohort and pooled placebo groups from RCTs with median NIHSS’ ~12 had achieved mRS 0-1 in 38% and 33% of the time, respectively.  A window into the lack of generalizability of the thrombolysis RCTs?  Perhaps – or just a curiosity.

Oh, but, back to the point – it does not appear to have clinical utility to routine use ceftriaxone as antibiotic prophylaxis after acute ischemic stroke.

“The Preventive Antibiotics in Stroke Study (PASS): a pragmatic randomised open-label masked endpoint clinical trial”
http://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736(14)62456-9.pdf

Should Men and Women Use Different Troponin Cut-Offs?

Much ado is made regarding potential differences in symptoms between men and women presenting with acute coronary symptoms.  Little is mentioned, however, about potential differences in laboratory thresholds between the sexes.  Considering women, on average, have decreased myocardial mass than men, any ischemic insult simply damages a smaller absolute quantity of myocardium.  Less damaged tissue, then, ought to lead to lower circulating biomarkers.

Why haven’t we tried this before?  Because the limit of detection of conventional troponin assays are above the clinically important thresholds for delineating such small quantities of circulating molecules.  However, with the advent of highly-sensitive troponins with reasonable precision below  the conventional troponin cut-off of 50 ng/L, it’s now a reasonable concept for investigation.

These authors conducted a yearlong prospective evaluation of all patients with suspected acute coronary syndrome, collecting conventional and highly-sensitive troponins on each.  Treating clinicians and initial adjudication of myocardial infarction were blinded to the results of the hsTnI.  Following conclusion of the study, records and unmasked hsTnI values were provided for independent adjudication and diagnosis changes accordingly.

Initially, 19% of men were diagnosed with Type 1 MI based on conventional troponin testing.  After using a gender-specific cut-off for men of 34 ng/L, only a handful of additional cases were re-classified – rising to 21%.  For women, 11% were initially diagnosed with Type 1 MI.  Using a gender-specific cut-off for hsTnI of 16 ng/L, however, doubled the diagnosis cohort to 22%.

Of course, simply lowering the threshold for any assay increases the rate of diagnosis.  In order to answer the question of whether the re-classified cases were clinically appropriate, all patients were also followed for survival free from death or MI.  While women not diagnosed with MI at initial presentation did well throughout the follow-up period, the women reclassified as MI using the hsTnI threshold suffered the same dismal outcomes as those initially diagnosed with MI.

I like this concept, and this is promising preliminary data.  It remains to be seen whether treatment, including increased treatment intensity for women, based on the gender-specific cut-offs changes clinical outcomes – or whether splitting these little nanograms worth of hairs is just overdiagnosis.  The good news: a clinical trial is ongoing.  I look forward to their results.

“High sensitivity cardiac troponin and the under-diagnosis of myocardial infarction in women: prospective cohort study”
http://www.bmj.com/content/350/bmj.g7873 (free fulltext)

Unreliable Information About Drug Use? In the ED? Never!

This simple observational series illuminates the likely truths behind our anecdotal experience – patients are either clueless or deliberately misleading regarding their ingestion of foreign substances.

For the purposes of this investigation, “drug use” is not restricted to illicit substances – these authors also explored the reliability of reporting of prescription medications.  In this prospective, year-long enrollment, 55 patients were selected randomly from a larger cohort to have a urine sample submitted for liquid chromatography/mass spectrometry.  The LC/MS assay utilized was capable of detecting 142 prescriptions, over-the-counter drugs, and drugs of abuse and their metabolites.  A drug whose level of detection was lower than 2 half-lives was reported as discordant with patient self-reporting.

All told, 17 out of 55 patients provided accurate medication histories, based on those detected on LC/MS.  Over half the patients under-reported – including a patient with 7 unreported drugs detected – while 29% over-reported a drug not subsequently detected.  Interestingly, illicit drugs were the least likely to be mis-reported, although, that may simply be a reflection of the higher prevalence of prescription and OTC medications.

Such observations are limited by the accuracy of the assay utilized, which has not been validated.  However, it ought come as no surprise many patients either intentionally or unintentionally misrepresent all possible drug exposures.  While not all omissions are clinically relevant, certainly, non-compliance and misinformation may have important implications for diagnosis and treatment.

“The Accuracy of Self-Reported Drug Ingestion Histories in Emergency Department Patients”
http://www.ncbi.nlm.nih.gov/pubmed/25052325

Prednisone … for Pneumonia?

The utility of antibiotics for eradication of bacterial pathogens from the lower respiratory tract is a given.  Use of steroids – also known for their immunosuppressive properties – not so much.

But, one can imagine clinical utility for steroids in acute infection.  Not every function of the immune system results in desirable patient-oriented effects.  Immunologic host responses include release of many inflammatory cytokines responsible for organ dysfunction, and steroids are already part of accepted therapy for several specific manifestations of pneumonia.  Based on prior results in smaller trials, these authors suspected use of steroids might be of benefit – both in mortality and in time to symptom resolution.

With 785 patients allocated in blinded fashion to 50 mg of prednisone daily or placebo, patients receiving prednisone reached “clinical stability” in a median of 3 days, compared to 4.4 days for the placebo cohort.  Hospital length-of-stay was reduced to 6 days from 7, and intravenous antibiotic use was cut by a day.  There were few important adverse effects overall, and the only consistent harm apparent in these data was increased hyperglycemia associated with corticosteroid use.

The accompanying editorial in The Lancet states adjunctive therapy with steroids is a therapy whose time has come, based on healthcare savings due to resource utilization.  In the context of other published studies, this observed reduction in time to vital sign normalization is valid.  However, whether the effect of steroids is truly beneficial or akin to simply masking the underlying clinical state by suppression of pro-inflammatory cytokine release is less certain.  Use of anti-pyretics blunts outward signs of systemic inflammatory response syndrome, and beta-blockers likewise reduce the tachycardia resulting from physiologic stress without specifically treating the underlying process.  It is hard to associate the outcomes measured in this trial with actual expedited clinical cure.

Reductions in length-of-stay and IV antibiotic use are reasonable patient-oriented and system-oriented outcomes, however, so the decision ultimately rests with the magnitude of harms – and the harms are certainly real.  Previous studies have suggested increased early recurrence or persistence of pneumonia, in addition to uncontrolled hyperglycemia.  These authors hoped to measure a 25% reduction in mortality – which was a bit of an odd expectation, given the ~2-4% expected absolute mortality – and no such suggestion of benefit was observed.

Simply put, this is not ready for prime-time or guideline-level adoption.  It is certainly worthy of further study, but steroids should not be used routinely outside the scope of prospective monitoring.

“Adjunct prednisone therapy for patients with community- acquired pneumonia: a multicentre, double-blind, randomised, placebo-controlled trial”
http://www.thelancet.com/journals/lancet/article/PIIS0140-6736(14)62447-8/abstract

NIHSS Scores are Not Created Equal

This is hardly news to anyone with a clinical practice, but it’s a topic rarely addressed in stroke trials – that patients with identical NIHSS can have a wide range of downstream disability.

This is a retrospective analysis of the VISTA registry, which collates non-thrombolysis acute stroke trial data, and is generally useful for identifying predictors of long-term prognosis and outcomes.  These authors used six hypothesized “profiles” of stroke syndromes with distinct constellations of disabilities, and matched a total of 10,271 patients from their database to one of the six.  Using their most disabling stroke subtype profile as reference, the authors noted three different syndromes – with median NIHSS 10, 9, and 7 – all had similar likelihood of favorable outcomes.  However, even though the NIHSS and good outcomes were similar, the disabilities and clinical profile associated with one of these cohorts translated to twice as likely to be deceased at 90 days.  In essence – similar “numbers”, but very different outcomes.

There’s nothing here usable for direct knowledge translation – but, it does hearken back to my oft-repeated statements regarding the heterogeneity of stroke syndromes, outcomes, and likelihood of benefit or harm from pharmacologic revascularization.  Quite simply, data sources such as this – and those including patients from thrombolysis trials – ought be better utilized to predict patient-specific outcomes.

“National Institutes of Health Stroke Scale Item Profiles as Predictor of Patient Outcome”
http://www.ncbi.nlm.nih.gov/pubmed/25503546