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SGEM#23: A Bump Up Ahead (Diagnosis of Appendicitis)

SGEM#23: A Bump Up Ahead (Diagnosis of Appendicitis)

Podcast Link:SGEM23
Date:  10 February 2013
Title: A Bump Up Ahead (Diagnosis of Appendicitis)

Case Scenario: 28yo woman presents to the ED at 2am with steadily increasing right lower quadrant (RLQ) pain. She has a past medical history of ovarian cysts. Her vital signs are stable, afebrile and tender over the RLQ. The blood work is unremarkable and specifically her pregnancy test is negative. Ultrasound and CT scan are not available overnight. What is your disposition and management of this patient?

Background: Undifferentiated abdominal pain is a high volume, high risk complaint. It represents approximately 7% of ED visits. Acute appendicitis is the second most common cause of malpractice litigation in children 6 – 17 years old.  Ten percent of all closed malpractice cases are due to missed diagnoses of appendicitis. It is not practical to image everyone with lower abdominal pain to rule out acute appendicitis in every case.

  • Lifetime acute appendicitis incidence is 8.6% in males and 6.7% in females
  • Lifetime appendectomy rates are 12% for males and 23.1% for females.
  • Negative laparotomy rate is 10-20%.
  • Appendectomy complications rate is 4-13%

Question: Does a bumpy car ride predict appendicitis?

Reference: F. Ashdown el al. Pain over speed bumps in diagnosis of acute appendicitis : A diagnostic accuracy study. BMJ Christmas Issue 2012

  • Population: Adults >16yrs referred to on-call surgery for assessment
  • 

Intervention: Speed bumps
  • Comparison: Migratory pain, nausea and vomiting, and rebound tenderness
  • Outcome: Sensitivity/specificity and likely hood ratios for appendicitis

Results: A total of 101 patients were included in this study. Sixty-eight reported driving over speed bumps on the way to the hospital. Four patients were excluded from the 68 (1-no histology available and 3-treated with antibiotics). Fifty four were “speed bump positive” of the 64.  The diagnosis of appendicitis was confirmed histologically in 33 or the 34 who reported worsened pain over speed bumps.  This gives a sensitivity of 97% (85% to 100%) and a specificity of 30% (15% to 49%). The positive predictive value (PPV) was 61% (47% to 74%), and the negative predictive value (NPV) was 90% (56% to 100%). The  positive likelihood ratio (LR) was 1.4 (1.1 to 1.8) and the negative LR was 0.1 (0.0 to 0.7).

Screen Shot 2013-02-09 at 2.46.23 PMScreen Shot 2013-02-09 at 2.46.09 PM

Additonal Resources:

Authors Conclusions: “Presence of pain while travelling over speed bumps was associated with an increased likelihood of acute appendicitis. As a diagnostic variable, it compared favourably with other features commonly used in clinical assessment. Asking about speed bumps may contribute to clinical assessment and could be useful in telephone assessment of patients.”

BEEM Commentary:

  • Anthony: Can not be generalized to a pediatric population and more pot-holes than speed bumps in Canada.
  • Jo-Ann: There was referral bias in this study because patients had to be referred to surgery to be included in the study.
  • Suneel: Likelihood ratios (LR) are a good way to present the results because LR are immune to prevalence of events.
  • Ken: Relatively small study (n=101) but inexpensive and no delay in lab turn around time.
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The Boys of the BEEM Dream Team: Ken, Suneel and Anthony

Jo-Ann Talbot

Jo-Ann Talbot

BEEM Bottom Line: Perhaps we should ask our patients if it was a bumpy ride to the ED and did the bumps hurt?

KEENER KONTEST: Yifan Li  from Western University correctly answered last weeks Keener question. Fixed-effect models assume only one true effect size. Thus, all differences in observed effects are due to sampling error. However, Random-effect models assume that your measurements draw from a random sample in a large population. Thus, the true effect varies from study to study and the variance tells us something about the large population.  The difference between them is interference. In the Fixed-effect model, you can only make inferences about your study population. In the Random-effect model, you can make inferences on the large population since you have taken random sampling into account.

Be sure to listen to the podcast to hear this weeks Keener Kontest question. Email your answer to TheSGEM@gmail.com. Use “Keener Kontest” in the subject line. First one to email me the correct answer will win a cool skeptical prize:)

Just came back from SkiBEEM 2013. We had a wonderful time and Silver Star Mountain in BC. Lots of people eager to cut the KT window to less than one year. Don’t Panic if you missed SkiBEEM. You can join us for SteeleBEEM 2013 Feb 21st and 22nd in Hamilton, Ontario.

Remember to be skeptical of anything you learn, even if you heard it on The Skeptics Guide to Emergency Medicine. Talk with you next week.

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  • Harry Wingate

    Ken and the BEEM dream team great work! I am enjoying the series. I have a new slogan for BEEM, sort of stolen from Papa John’s Piza.

    How about this…

    “Better care, lower cost, better outcomes….BEEM”

    Tripp Wingate MD, FACEP

  • ken

    Thanks Tripp. We had fun doing the show as a group. Stay tuned for this next weeks issue. TheSGEM does not shy away from controversial topics. We have done emergency contraception. Now TheSGEM will start into the issue of stroke…

  • Aidan Findlater

    I’ve been catching up on old podcasts and just wanted to correct something I heard on this one. Sensitivity and specificity are not affected by the prevalence of disease in the population. That’s why they’re the numbers that are used when discussing the accuracy of diagnostic tests, instead of using the more intuitive positive and negative predictive values. The likelihood ratios are calculated from the sensitivity and specificity, so anything that affects sensitivity and specificity will affect the LRs as well.

    I think that referral bias is usually used to refer to something else, but it’s been a while.

    • http://www.thesgem.com admin

      Aidan:
      thanks for the comments. I will put one of our BEEM Dream Team members (Suneel) who was on the group podcast to respond.
      Ken

    • http://www.thesgem.com admin

      Hello Aidan,

      You are correct that Sens and Spec are not necessarily affected by the prevalence of the disease because they are straight ratios from the various cells in the diagnostic 2×2 table…However, PPV and NPV will be influenced by prevalence…You are also correct in that likelihood ratios are not affected by prevalence as the values of Sens and Spec are directly involved in these formulas, not the PPV/NPV values…

      For your clarification, I have attached a copy of the best article that explains these concepts very simply, written by a colleague here at McMaster…It explains everything perfectly for you…

      Hope this helps…

      Suneel U.

    • ken

      Hello Aidan,

      You are correct that Sens and Spec are not necessarily affected by the prevalence of the disease because they are straight ratios from the various cells in the diagnostic 2×2 table…However, PPV and NPV will be influenced by prevalence…You are also correct in that likelihood ratios are not affected by prevalence as the values of Sens and Spec are directly involved in these formulas, not the PPV/NPV values…

      For your clarification, I have attached a copy of the best article that explains these concepts very simply, written by a colleague here at McMaster…It explains everything perfectly for you…

      Hope this helps…

      Suneel U.

      • Reuben G.

        Good evening all,

        I had the same thoughts as Aidan as I heard the podcast. However, thought I’d look it up first and came across the following link to a recent article from six months ago which states that, despite our belief that Sens and Spec (and therefore LR) should not be affected by prevalence, they might be!
        http://www.ncbi.nlm.nih.gov/pubmed/23798453

        And that’s a KT of 7 months ;)

        However, may I say that, assuming I did not misunderstand, the definition that Ass.Prof Talbot gives for sensitivity is ACTUALLY the definition for PPV (think she says that sens is the True positive out of the total positives!)

        Nitpicking aside, can I just say this podcast is a relatively new discovery for me and it’s an absolute gem, as precious as the SMACC and EMCRIT podcasts! Please don’t ever stop and keep ‘em coming!!

        PS Is there an efficient way of knowing exactly when you’ve thrown a keener kontest gauntlet: I’m dying to be the first Maltese and the first (I think!) European EM trainee to win the SGEM prize!! :)

        Thanks again
        Reuben

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