When I was at Bellvue (New York) the commonest paediatric emergency on
the paediatric surgical ward was convulsions due to hyponatraemia.
The positive appendicectomy rate was 100%.
I don't recall the precise figure for ruptured appendix and peritonitis
- but it wasn't far off 100%.
Patients were dripped (with D5W) and sucked and on day 5 they convulsed.
I hope the Sheffield algorithm did better that Bellevue in the late
1960s!
In message
<!&!AAAAAAAAAAAYAAAAAAAAAEeN/GyWFTROuuxPR1kecbbCgAAAEAAAAGQQo/xGeHtPjL0v2
[log in to unmask]>, Saul Galloway <[log in to unmask]> writes
>>Why are we not using them to sort patients into those who deserve a
>>second look because they are sort of like someone who had a bad outcome
>>recently?
>
>We are, aka the experienced GP. Even on a good day I'm just a well paid
>pattern recognition engine, and most of my data inputs are unconscious. I
>used to worry about my rule set getting fuzzier and fuzzier but more and
>more I think (hope) it's an inevitable function of volume of data (in this
>context patient consultations). At it's most extreme this gets as
>inexplicable as the consultant that asks for a serum calcium on patient
>presenting with headache, because he once saw another bloke called Pettifer
>about the same age with a similar thing and he had a stutter too.
>
>Sometimes there are spectacular mismatches. If you feed in :
>
>TATT
>Insomnia
>Irritable
>Tense
>Marital difficulties
>Errectile dysfunction
>Work stress
>
>into my algorithm (actually this makes me wonder if verbal consultations
>couldn't be deconstructed into key words just like a spam filter)I'm up a
>ladder of inference so high I can't see the ground, which of course kicks
>into play a particular "filter" of expectation.
>
>About 30 years ago at Sheffield Childrens Hospital they were trying to
>design an algorithm to help diagnosing the acute abdomen. You fed in the
>WCC, temp, ticked the box for aspects of history etc. and the system as
>supposed to learn from the outcome and recursively (I think) weight the
>presenting features.
>
>What you got though was a differential in the form
>
>69% mesenteric adenitis
>20% functional
>11% appendicitis
>
>which was surprisingly little use in the decision of whether or not to do an
>appendectomy. The bit that would be could would be the "this symptom
>combination is 90% likely to be <commonish condition> as you correctly
>diagnosed, but please also consider the 0.01% chance of <Von Eponymausens
>syndrome> which commonly has the feature <indentifier>
>
>
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