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Record W3183668890 · doi:10.1111/acem.13238

Hot Off the Press: Which Febrile Children With Sickle Cell Disease Need a Chest X‐ray?

2017· letter· en· W3183668890 on OpenAlexaff
Justin Morgenstern, Corey Heitz, William K. Milne

Bibliographic record

VenueAcademic Emergency Medicine · 2017
Typeletter
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsWestern UniversityMarkham Stouffville Hospital
Fundersnot available
KeywordsMedicineEmergency departmentForearmConfidence intervalLikelihood ratios in diagnostic testingGold standard (test)Prospective cohort studyPediatricsPopulationPhysical therapySurgeryInternal medicine

Abstract

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Pediatric musculoskeletal injuries are seen frequently in the emergency department (ED). Between 25 and 50% of all children will sustain a fracture before the age of 16, with the distal forearm being the most common location to fracture.1-3 The traditional diagnostic approach uses x-ray to identify fractures, but obtaining x-rays can be painful, as well as adding time and cost to ED visits.4, 5 Recently, there has been interest in the use of point-of-care ultrasound (POCUS) to diagnosis pediatric fractures, but the inclusion of children with clinically obvious deformities may have overestimated ultrasound accuracy in previous trials.6−9 This study aims to determine the sensitivity of POCUS for nonangulated pediatric forearm fractures, while also measuring patient important outcomes such as pain, caregiver satisfaction, and procedure duration.10 This prospective, cross-sectional diagnostic study examined the performance of POCUS in the diagnosis of suspected nonangulated forearm fractures in pediatric patients aged 4–17 years. X-ray was considered the criterion standard. The test characteristics reported are a sensitivity of 94.7% (95% confidence interval [CI] = 89.7%–99.8%), a specificity of 93.5% (95% CI = 88.6%–98.5%), a positive likelihood ratio of 14.6, and a negative likelihood ratio of 0.6. This was a well-done diagnostic study, with a clearly defined patient population based in the ED, in which all patients underwent both the study test (POCUS) and a clinical standard (x-ray). There are some limitations. A convenience sample was used, which could result in selection bias if the included patients were in some way different from those who were not included. The accuracy of POCUS is user-dependent. The use of expert sonographers in this study provides a look at the accuracy of POCUS in ideal circumstances, but limits generalizability, as the average emergency physician may not possess these skills. On the other hand, sonographers were blinded to injury mechanism. Although this provides us with a more accurate look at POCUS in isolation, it may underestimate the diagnostic value of POCUS in practice, where images are guided and interpreted in the context of the history and physical examination. There is also a question of what constitutes the ideal criterion standard for fractures. X-ray was used as the criterion standard in this study, but we know that x-rays are imperfect. There were six factures identified by POCUS that were deemed false positives based on the x-ray results. However, it is possible these were real fractures that were missed by x-ray, but without clinical follow-up we cannot know. Similarly, without clinical follow-up, this study cannot tell us if the injuries missed by POCUS were clinically important. There were four missed injuries: one buckle fracture and three ulnar styloid fractures. If POCUS is going to be widely used to diagnose fractures, it would be ideal to see a randomized controlled trial comparing POCUS to x-ray as the initial diagnostic strategy and focusing on clinical outcomes in follow up as the primary outcome. A total of 169 children were enrolled in the study and 76 (45%) were diagnosed with fractures. The mean age was 11 years with 52% being male. Most fractures (80.3%) were buckle fractures. Sensitivity of POCUS (the primary outcome) was 94.7% (95% CI = 89.7%–99.8%). The remaining test characteristics for POCUS were a specificity of 93.5% (95% CI = 88.6%–98.5%), positive predictive value of 92.3% (95% CI = 86.4%–98.2%), a negative predictive value of 95.6% (95% CI = 91.4%–99.8%), a positive likelihood ratio of 14.6, and a negative likelihood ratio of 0.6. Inter-rater agreement between the bedside ultrasonography and an expert sonographer reviewing the images is reported as excellent, with a kappa of 0.74. As compared to x-ray, patients reported less pain with POCUS. Ninety percent of caregivers were “satisfied” or “very satisfied” with POCUS. Acute musculoskeletal injuries are common in pediatrics and accurate diagnosis is important. This study illustrates that POCUS, when performed by experienced sonographers, has a high diagnostic accuracy for nonangulated distal forearm fractures, but will miss some fractures. It is valuable to know that POCUS takes less time than x-rays, has a low level of reported pain, and has a high level of caregiver satisfaction. Although POCUS probably has a role in some clinical settings, these results do not support widespread adoption as a replacement for x-ray. Casey Parker: This is another paper showing that POCUS can give us good, rapid information. It remains difficult to use US purely in practice as our teams and orthopedic colleagues remain “in the dark.” I have a few comments/questions about the paper: Dr. Poonai's reply: Thanks for the comments and tips, Casey. Here are my responses: 1) You're correct that in the clinical setting we incorporate a history and exam but blinding was incorporated into the protocol so as not to inflate the test performance characteristics. 2) There were no data on these as we took the pediatric radiologist's interpretation as the criterion standard. Not all children receive follow-up x-rays. Dr. Poonai's reply: Interesting question, Dara. This is a great example of the clinical context in which many POCUS aficionados find the technology to be quite useful. Although adequately powered, I will admit that our study was small to moderately sized and, at this stage, I may be reluctant to use POCUS exclusively to rule out a fracture. However, our specificity was quite high, suggesting that if a fracture is seen on POCUS, the x-ray may not be needed. This depends on obtaining a reliable history from the child with respect to the mechanism of injury (read: consistent with injury pattern so as not to miss NAI) and location of the pain. Hope that helps. Eve Purdy: Thanks for the great episode. I am very skeptical that our orthopedic colleagues (at least where I work) would be keen for this to be used as a replacement for X-ray—although I certainly can see why and how it would be useful in different settings explored (LMIC, camps, etc.). Dr. Poonai's reply: You've made some great points, Eve. And yes, I fully agree that practice patterns across institutions, healthcare systems, and countries are important consideration in how the results of our study impact practice. As far as medicolegal issues, at our center, image acquisition (stills or video clips) using POCUS are uploaded onto a central registry called Qpath. From there, images can be read, annotated, and archived. This may be one avenue for ensuring that there's a paper trail. Pediatric forearm fractures can be assessed quickly and with minimal pain using POCUS in the ED. The accuracy is good, but with a sensitivity of 95% in expert hands, POCUS is probably not ready for routine use. For best accuracy, POCUS results should be always considered in the context of the history and physical examination.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.052
GPT teacher head0.346
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2017
Admission routes1
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