Category: Uncategorized

Which Sepsis Alert is the Biggest Loser?

It’s a trick question – in the end, all of us have already lost.

This is a short retrospective report evaluating, primarily, the Epic Sepsis Prediction Model, and the mode in which is deployed. The Epic SPM generates a “prediction of sepsis score”, calculated at 15 minute intervals, providing a continuous risk score for the development of sepsis. Of course, in modern medicine, this is usually reduced to a trigger threshold at which point an alert is fired. Alerts, alerts, alerts – what are they good for?

In this study, the Epic SPM was evaluated at several difference SPS score thresholds ranging from ≥5 to ≥10 – and compared, as well, with SIRS, qSOFA, and SOFA. There were two goals for the evaluation: accuracy and timeliness. All prediction tools provided the same age-old tradeoff between sensitivity and specificity, with a PSS of ≥5 being 95% sensitive, but merely 53% specific. Likewise, a more specific cut-off sacrificed sensitivity. SIRS, qSOFA, and SOFA suffered from the same limitations.

The “time to detection” was a bit more interesting, but conclusions are a bit limited by the methods used to determine. The PSS is calculated at 15 minute intervals, while their calculations of SIRS, qSOFA, and SOFA all happened at hourly intervals. Then, “time zero” for their calculations was actually determined by the time of clinician action – the time at which a clinician suspected sepsis and ordered either antimicrobials or blood cultures. With respect to timeliness, only a minority of patients met threshold scores at “time zero” – except SIRS, where nearly half were at threshold.

So, it’s hard to conclude much from these data – other than, as previously alluded, we are all losers. These alerts are clearly useless, yet they, and the Surviving Sepsis bundle gestapo have trained clinicians to leap at the earliest opportunity to (over)diagnose sepsis and administer broad-spectrum antibiotics. Multiple specialty societies have asked for the SEP-1 measures to be rolled back due to these obvious harms, let alone the administrative costs, and eliminating that “quality” measure would go a long way to putting these useless alerts to bed.

Sepsis Prediction Model for “Determining Sepsis vs SIRS, qSOFA, and SOFA”

Anchoring on Bias

The results of this paper are hardly surprising, since the witnessed phenomenon – “anchoring bias” – exists as defined. However, it’s always fun to see it demonstrated objectively.

In this little piece of research, authors collated four years of encounters to Veterans Affairs emergency departments in the U.S. and parsed out the triage reason between “congestive heart failure” versus all others. These two groups were then compared regarding the rates of objective testing for pulmonary embolism, frequency of ordering B-type natiuretic peptide, and both initial and 30-day diagnoses of pulmonary embolism.

As the title suggests, the authors identify differences in testing associated with the recorded reason for visit – with less frequent testing for PE, increased confirmatory testing for CHF, and fewer diagnoses of PE at the initial visit. However, the 30-day rate of diagnosis for PE was the same between the two groups – 1.2% in those initially presenting for reason of CHF, and 1.1% for all others.

The implication suggested by these authors is the subsequent similar frequency of PE at 30 days represent a delayed or missed initial diagnosis, with the culprit being an element of cueing from the patient triage reason or other elements of medical history. This is obviously not a study design with the ability to conclusively demonstrate such a causative effect; a prospective design randomizing patients with an initial “CHF” reasons for visit to an alternative such as “shortness of breath” would tease out this effect. That said, this likely still represents an undercurrent of anchoring bias.

“Evidence for Anchoring Bias During Physician Decision-Making”
https://jamanetwork.com/journals/jamainternalmedicine/article-abstract/2806464

Fall Recap

It is the long, cold dark here in Christchurch – improved dramatically by leaving for the U.S. for four weeks!

Firstly, the blog may be making a bit of a comeback – the ugly demise of Twitter seems to necessitate a better method of knowledge translation, such as blog posts that can be replicated across whichever platform is progressing towards dominance.

Next, of course, the Annals of Emergency Medicine Podcast continues apace. We’ve had two excellent co-hosts these past months whose background is far more diverse than ourselves, and we will be continuing to feature additional guests in coming months.

What have I been putting into ACEPNow?

Lastly, the Annals of Emergency Medicine Journal Club features important articles from outside the Emergency Medicine literature:

Summer Recap

Down here, summer has ended – although, you wouldn’t know it from the 26C weather we’re having outside today.

But, this means it’s been a few months since I’ve linked to my various #FOAMed resources around the web.

First, and not least, the Annals of Emergency Medicine Podcast, the Ryan and Rory Show, recapping the articles from each month’s issue, available for free on your choice of streaming platforms:

Then, there’s always something to learn from ACEP Now!

Finally, not every article relevant to Emergency Medicine lands in an EM journal – hence the Annals of Emergency Medicine Journal Club. Here are a few of the highlights from around the remaining published literature we’ve looked at recently:

Finally, a Twitter thread with slides illustrating some of the top articles of 2022:

Enjoy!

April Update

Just a quick update to the blog to collate various items from around the web.

The Annals of Emergency Medicine monthly podcast is updated through February 2022, freely available from your choice of services:

Likewise, the Annals of Emergency Medicine Journal Club is freely available:

Finally, a couple more pieces from ACEPNow, highlighting recent scientific developments and my experience in a universal healthcare system:

2021 Wrap-Up

A few items to collate from the last several months’ efforts.

The Annals of Emergency Medicine Podcast continues apace, with free monthly updates from the original research published in the journal:

Likewise, the Annals of Emergency Medicine Journal Club has published several monthly installments:

Two more pieces in ACEPNow:

And, finally, from a talk I gave our ACEM trainees – the list of included articles, highlighting some of the most interesting articles published in 2021:

The Use of Tranexamic Acid to Reduce the Need for Nasal Packing in Epistaxis (NoPAC): Randomized Controlled Trial
No advantage to routine use of topical TXA for epistaxis.
https://doi.org/10.1016/j.annemergmed.2020.12.013

Ultra-early tranexamic acid after subarachnoid haemorrhage (ULTRA): a randomised controlled trial
No advantage to routine use of IV TXA for aneurysmal SAH.
https://doi.org/10.1016/S0140-6736(20)32518-6

Effect of Endovascular Treatment Alone vs Intravenous Alteplase Plus Endovascular Treatment on Functional Independence in Patients With Acute Ischemic Stroke
Stopped early due poor outcomes in patients receiving alteplase prior to endovascular therapy.
https://jamanetwork.com/journals/jama/fullarticle/10.1001/jama.2020.23523

A Randomized Trial of Intravenous Alteplase before Endovascular Treatment for Stroke
Heterogenous outcomes showing a small advantage, primarily recanalization, in patients receiving alteplase prior to endovascular therapy.
https://doi.org/10.1056/NEJMoa2107727

Effect of Mechanical Thrombectomy Without vs With Intravenous
Thrombolysis on Functional Outcome Among Patients With Acute Ischemic Stroke
No reliable differences between patients regardless of therapy.
https://doi.org/10.1001/jama.2020.23522

Prospective, Multicenter, Controlled Trial of Mobile Stroke Units
A “mobile stroke unit” administered tPA more rapidly, demonstrating an association with improved outcomes – the entire effect size made up of “Stroke reversed by tPA”.
https://doi.org/10.1056/NEJMoa2103879

Effect of Intravenous Fluid Treatment With a Balanced Solution vs 0.9% Saline Solution on Mortality in Critically Ill Patients
No patient-oriented difference in outcomes regardless of fluid choice, although resuscitation volumes were not excessive.
https://doi.org/10.1001/jama.2021.11684

Short-Course Antimicrobial Therapy for Pediatric Community-Acquired Pneumonia
5 days of high-dose amoxicillin was no different than 10 days of high-dose amoxicillin.
https://doi.org/10.1001/jamapediatrics.2020.6735

Effect of Amoxicillin Dose and Treatment Duration on the Need for Antibiotic Re-treatment in Children With Community-Acquired Pneumonia
No difference between 3 days vs. 7 days, nor between high-dose or low-dose amoxicillin.
https://doi.org/10.1001/jama.2021.17843

Delayed Antibiotic Prescription for Children With Respiratory Infections: A Randomized Trial
“Delayed” antibiotic prescribe was a safe strategy for reducing inappropriate antibiotic treatment – but so was “no” antibiotics.
https://doi.org/10.1542/peds.2020-1323

Effect of Oral Moxifloxacin vs Intravenous Ertapenem Plus Oral Levofloxacin for Treatment of Uncomplicated Acute Appendicitis
Outcomes in patients with appendicitis managed with antibiotics were similar regardless of whether patients began with oral antibiotics or started with intravenous and then transitions to oral.
https://doi.org/10.1001/jama.2020.23525

Antibiotics versus Appendectomy for Acute Appendicitis — Longer-Term Outcomes
Within 90 days, 29% of patients managed with antibiotics underwent appendectomy. At 1 year, 46%; 2 years, 46%, 3 and 4 years, 49%.
https://doi.org/10.1056/NEJMc2116018

Effect of Use of a Bougie vs Endotracheal Tube With Stylet on Successful Intubation on the First Attempt Among Critically Ill Patients Undergoing Tracheal Intubation
First-pass intubation success was ~83% for trainees using video laryngoscopy, regardless of using bougie or stylet for ET tube.
https://doi.org/10.1001/jama.2021.22002

Effect of Moderate vs Mild Therapeutic Hypothermia on Mortality and Neurologic Outcomes in Comatose Survivors of Out-of-Hospital Cardiac Arrest
31°C was no better than 34°C for improving neurologic outcomes following OHCA.
https://doi.org/10.1001/jama.2021.15703

Hypothermia versus Normothermia after Out-of-Hospital Cardiac Arrest
Hypothermia, under the conditions typically implemented in major centers, did not improve neurologic outcomes following OHCA.
https://doi.org/10.1056/NEJMoa2100591

Angiography after Out-of-Hospital Cardiac Arrest without ST-Segment Elevation
An RCT showing no advantage to routine immediate angiography in non-STEMI OHCA.
https://doi.org/10.1056/NEJMoa2101909

Pathway with single-dose long-acting intravenous antibiotic reduces emergency department hospitalizations of patients with skin infections
A sponsor encouraging discharge of patients with SSTI results in discharge of patients with SSTI.
https://doi.org/10.1111/acem.14258

Self-obtained vaginal swabs are not inferior to provider- performed endocervical sampling for emergency department diagnosis of Neisseria gonorrhoeae and Chlamydia trachomatis
A woman can self-swab for STI every bit as effectively as a clinician performing a pelvic examination.
https://doi.org/10.1111/acem.14213

Invasive Bacterial Infections in Afebrile Infants Diagnosed With Acute Otitis Media
Afebrile infants ≤ 90 days diagnosed with AOM do not seem to be at risk for IBI.
https://doi.org/10.1542/peds.2020-1571

Effect of Vasopressin and Methylprednisolone vs Placebo on Return of Spontaneous Circulation in Patients With In-Hospital Cardiac Arrest
An IHCA protocol incorporating vasopressin and methylprednisolone improved immediate outcomes, but not hospital discharge.
https://doi.org/10.1001/jama.2021.16628

Risk for Recurrent Venous Thromboembolism in Patients With Subsegmental Pulmonary Embolism Managed Without Anticoagulation
Non-trivial rates of recurrent VTE, particularly in the elderly and those with multiple SSPE, mean anticoagulation is likely indicated.
https://doi.org/10.7326/M21-2981

Effect of a Diagnostic Strategy Using an Elevated and Age-Adjusted D-Dimer Threshold on Thromboembolic Events in Emergency Department Patients With Suspected Pulmonary Embolism
Another successful example of adjusting D-dimer thresholds, this time combining pretest likelihood and age.
https://doi.org/10.1001/jama.2021.20750

Outpatient Management of Patients Following Diagnosis of Acute Pulmonary Embolism
Of the few low-risk patients with PE managed as outpatients in the U.S., the subsequent hospitalization rate was around 10%.
https://doi.org/10.1111/acem.14181

Rapid Administration of Methoxyflurane to Patients in the Emergency Department (RAMPED) Study: A Randomized Controlled Trial of Methoxyflurane Versus Standard Care
More patients treated with methoxyflurane had reductions in pain, but more patients in the methoxyflurane arm received oral and/or parenteral opioids.
https://doi.org/10.1111/acem.14144

Repeat head computed tomography for anticoagulated patients with an initial negative scan is not cost-effective
Only 1% of patients on anticoagulation with an initial negative head CT developed subsequent ICH, none of whom developed symptoms or required intervention.
https://doi.org/10.1016/j.surg.2021.02.024

Risk of Traumatic Brain Injuries in Infants Younger than 3 Months With Minor Blunt Head Trauma
2+% of infants aged less than 3 months meeting PECARN low-risk criteria still had ICH, although only 1 – 0.2% – was clinically important.
https://doi.org/10.1016/j.annemergmed.2021.04.015

Impact of oral corticosteroids on respiratory outcomes in acute preschool wheeze: a randomised clinical trial
Prednisolone hastens improvement in wheezing and reduced hospital admission, while symptoms were equivalent by 24 hours, regardless.
https://doi.org/10.1136/archdischild-2020-318971

Association of Intravenous Radiocontrast With Kidney Function
An interesting analysis centered around the dichotomous D-dimer cut-off for CTPA found no association of contrast exposure with follow-up eGFR.
https://doi.org/10.1001/jamainternmed.2021.0916

Maximizing the Morning Commute: A Randomized Trial Assessing the Effect of Driving on Podcast Knowledge Acquisition and Retention
Similar knowledge retention resulted from podcast listening whether attention was focused or during driving.
https://doi.org/10.1016/j.annemergmed.2021.02.030

Still Alive!

While the blog has become a bit sparse – owing to the demands of a new environment down in New Zealand – I’ve got plenty of new content to share.

I’m still writing bimonthly for ACEPNow:

Then, every month there’s a new Annals of Emergency Medicine Journal Club:

Finally, the Annals of Emergency Medicine Podcast is available on your choice of platform:

Enjoy!

The United Colors of Sepsis

Here it is: sepsis writ Big Data.

And, considering it’s Big Data, it’s also a big publication: a 15 page primary publication, plus 90+ pages of online supplement – dense with figures, raw data, and methods both routine and novel for the evaluation of large data sets.

At the minimum, to put a general handle on it, this work primarily demonstrates the heterogeneity of sepsis. As any clinician knows, “sepsis” – with its ever-morphing definition – ranges widely from those generally well in the Emergency Department to those critically ill in the Intensive Care Unit. In an academic sense, this means the patients enrolled and evaluated in various trials for the treatment of sepsis may be quite different from one another, and results seen in one trial or setting may generalize poorly to another. This has obvious implications when trying to determine a general set of care guidelines from these disparate bits of data, and resulting in further issues down the road when said guidelines become enshrined in quality measures.

Overall, these authors ultimately define four phenotypes of sepsis, helpfully assigned descriptive labels using the letters of the greek alphabet. These four phenotypes of sepsis are derived from retrospective administrative data, then validated on additional retrospective administrative data, and finally the raw data from several prominent clinical trials in sepsis, including ACCESS, PROWESS, and ProCESS. The four phenotypes were derived by clustering and refinement, and are described by the authors as effectively: a mild type with low mortality; a cohort of those with chronic illness; a cohort with systemic inflammation and pulmonary disease; and a final cohort with liver dysfunction, shock, and high mortality.

We are quite far, however, from needing to apply these phenotypes in a clinical fashion. Any classification model is highly dependent upon the inputs, and in this study the inputs are the sorts of routine clinical data available from the electronic health record: vital signs, demographics, and basic labs. Missing data was common, including, for example, lactate levels, which was not obtained on 80% of patients in their model. These inputs then dictate how many different clusters you obtain, how the relative accuracy of classification diminishes with greater numbers of clusters, as well whether the model begins to overfit the derivation data set.

Then, this is a little bit of a fuzzy application in the sense these data represent as much different types of patients with sepsis, as it represents different types of sepsis. Consider the varying etiologies of sepsis, including influenza pneumonia, streptococcal toxic shock, or gram-negative bacteremia. These different etiologies would obviously result in different host responses depending on individual patient features. These phenotypes derived here effectively mash up causative agent with the underlying host, muddying clinical application.

If clinical utility is limited, then what might the best utility for this work? Well, this goes back to the idea above regarding translating work from clinical trials to different settings. A community Emergency Department might primarily see alpha-sepsis, a community ICU might see a lot of beta-sepsis, while an academic ICU might see predominantly delta-sepsis. These are important concepts to consider – and potentially subgroup-analyses to perform – when evaluating the outcomes of clinical trials. These authors do several simulations of clinical trials while varying the composition of phenotypes of sepsis, and note potentially important effects on primary outcomes. Pathways of care or resuscitation protocols could potentially be more readily compared between trial populations if these phenotypes were calculated.

This is a challenging work to process – but an important first step in better recognizing the heterogeneity in potential benefits and harms resulting from various interventions. The accompanying editorial does really a very excellent job of describing their methods, outcomes, and utility, as well.

“Derivation, Validation, and Potential Treatment Implications of Novel Clinical Phenotypes for Sepsis”
https://jamanetwork.com/journals/jama/fullarticle/2733996

“New Phenotypes for Sepsis”
https://jamanetwork.com/journals/jama/fullarticle/2733994

The “Fragility Index” in Emergency Medicine

This little paper is an interesting look at trials in Emergency Medicine and their robustness – or lack thereof.

The “fragility index“, as described by its proprietors, is effectively a “number needed to treat” for confidence intervals and p-values. In simplest form, the fragility index is the number of patients needed to change their primary outcome in order to nullify an otherwise statistically significant result. Effectively, if a trial result would change if only two patients had different outcomes, the fragility would be 2 – and this would reflect a trial whose results are not terribly robust.

The authors then go on to use their tool to evaluate 180 trials across emergency medicine and emergency medicine journals. The medial fragility index across all trials: 4. Of course, this is not terribly unexpected, as the median sample size across all trials was only 140 – not usually enough to illuminate a reliable result except in only the most impressive of effect sizes.

The tool itself is not a novel reinvention of statistical significance or analysis, but just another mechanism for knowledge translation to reflect the relative stability or robustness of a result from a trial. Interpretation of frequentist statistics, p-values, and confidence intervals can frequently be rather opaque or misleading, and reporting a fragility index can be considered one approach to conceptualizing the strength of a result. The real solution, also noted by these authors, is simply to interpret individual trial results in a Bayesian context – adding one trial to a Bayesian prior, when available, to see how a trial shifts the current evidence.

“The Results of Randomized Controlled Trials in Emergency Medicine Are Frequently Fragile”

https://www.ncbi.nlm.nih.gov/pubmed/30551894

Lactate is Dead! Long Live Lactate?

Our use of serum lactates as targets for resuscitation in sepsis is more than a little flawed. Once upon a time, we resuscitated using central venous oxygenation as part of the Rivers’ trial. Whether those targets were actually a valid part of the multi-pronged bundle remains an excellent and open question. Of course, CVO2 requires invasive monitoring – and serum lactate became our less-invasive surrogate. And, yes, patients with high lactates do poorly – but that doesn’t specifically address the assumption lactate-guided resuscitation is tied to outcomes, or the optimal resuscitation strategy.

This multi-center trial out of Latin America looks at another marker of perfusion status, capillary refill time, that is likewise observationally associated with mortality in sepsis. In a randomized, open-label trial, the first eight hours of resuscitation was guided either by lactate levels or capillary refill time. Resuscitation in both arms used a specific protocol of fluids, fluid-responsiveness assessments, vasopressors, and inodilators.

Without unpacking these specifics in too great of detail, as will be done by many other critical care physicians, the results are quite interesting: of 424 patients randomized, they observed 34.9% mortality in the CRT-guided cohort compared with 43.4% in the lactate-guided cohort. Other secondary outcomes, including lactates at 48 and 72 hours, SOFA scores at 72 hours, generally favored the CRT cohort.

Is this the end of lacate? Certainly, in a resource austere setting, it would generally indicate there’s no rush to adopt lactate use in the context of a just-as-good, zero-cost means of assessment. The accompanying editorial wonders aloud: why not use both? While this seems like a reasonable idea, it probably doesn’t go far enough – why not use all the data for an individual patient to determine their optimal treatment, rather than our current one-size-fits-all nuclear option? Reliance on any single approach to resuscitation – perhaps mandated by “quality” measures – is almost certain to be short-sighted. While I do not advocate a return to the wild west of late recognition and neglect, these data should add further fuel to a reassessment of our golden idols and targets in the treatment of sepsis.

“Perfusion Status vs Serum Lactate Levels on 28-Day Mortality Among Patients With Septic Shock: The ANDROMEDA-SHOCK Randomized Clinical Trial”

https://jamanetwork.com/journals/jama/fullarticle/2724361