Less life threatening differential diagnoses

Vipindas Chengat syncopesystem at GMAIL.COM
Mon Aug 3 03:49:42 UTC 2015


We do use similar principles.

Vipin

*Vipindas Chengat, MD FACP**  |  *Chairman, Physician Cognition, Inc.
  —————————————————————————————————
  Mobile: +1 (773) 575-3550
  Email: Vipin at PhysicianCognition.Com <Vipin at PhysicianCognition.com>
  Website: PhysicianCognition.Com <http://physiciancognition.com/>



On Sun, Aug 2, 2015 at 9:17 PM, Alan Morris <Alan.Morris at imail.org> wrote:

> Is your algorithm linked in any way with Larry Weed’s strategy and his
> knowledge couplers?
> Alan H. Morris, M.D.
> Professor of Medicine
> Adjunct Prof. of Medical Informatics
> University of Utah
>
> Director of Research
> Pulmonary/Critical Care Division
> Sorenson Heart & Lung Center - 6th Floor
> Intermountain Medical Center
> 5121 South Cottonwood Street
> Murray, Utah  84157-7000, USA
>
> Office Phone: 801-507-4603
> Mobile Phone: 801-718-1283
>
>
> From: Vipindas Chengat <syncopesystem at GMAIL.COM>
> Reply-To: Society to Improve Diagnosis in Medicine <
> IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG>, Vipindas Chengat <
> syncopesystem at GMAIL.COM>
> Date: Sunday, August 2, 2015 at 19:57
> To: "IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG" <
> IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG>
>
> Subject: Re: [IMPROVEDX] Less life threatening differential diagnoses
>
> Excellent questions. Here are my thoughts.
>
> 1. With fever and cough, how much likely does the patient have pneumonia.
>
>  What if the answer is 76%? For epidemiological data for an ER or an
> insurance company, it is a valid information. But, for a clinician, he/she
> has only one patient at a time and does not know if that patient belongs to
> 76% or 24 % or 5%. So, how can this be a relevant number unless he/ she has
> gathered all relevant clinical information for that combination of
> symptoms?
>
> 2. What if the cough is chronic and fever is intermittent for months? What
> if the patient has fever, cough, night sweats, weight loss and
> lymphadenopathy? Or fever for two days and cough for months? To consider
> every single possibility, how many patients should be studied and for how
> long?
>
> 3. Say, if the patient has cervical lymphadenopathy and analysis has shown
> that there is 5% chance of having lymphoma. What does that 5% mean? Whether
> the physician should do biopsy or wait? Whether the patient be happy or
> unhappy as the number can be perceived as high or low depends on
> individuals. Rather, shouldn't the physician try to gather data like the
> size and consistency of the LN, presence of systemic signs etc?
>
> 4. Our algorithm create dynamic checklists. Example: What if fever and
> cough has started after chest trauma or an episode of seizure? These are
> specific contexts that are relevant for that combination. It can also look
> for other symptoms like purulent sputum or hemoptysis or unilateral leg
> swelling.
>
> 5. The study that you have mentioned can be used for one diagnosis at a
> time. However, what if there are hundreds of diagnoses for a combination of
> symptoms? Example, if you suspect PE, you can calculate pre test
> probability and then order d dimer or CT angiogram or VQ scan and evaluate
> the post test probability based on the performance characteristic of the
> test. However, is PE missed due to lack of awareness of the literature or
> inability to consider it for uncommon presentations like unexplained
> tachycardia? Is diagnosis missed due to lack of availability of data based
> on multivariate analysis or inability to see patterns and inability to
> gather all the relevant clinical data before making diagnostic assumptions?
>
> 6. If I input fever and cough for a 40 year old man, my algorithm
> considers all the possible causes- several hundreds and list them in the
> order of relevance. How does it test for relevance? How do we get the pre-
> test probability ? Well, even practicing physicians don't know what the
> exact pre test probability is. We don't try to solve it purely
> mathematically. We aren't rounding with tables with LRs and sensitivity/
> specificity. But, we do have an understanding that some are common and some
> are rare. Some symptoms and signs and very specific and some are not. To
> consider certain diagnoses, we absolutely need certain symptoms. We know
> what questions and to ask and try to find patterns that are relevant based
> on patho-physiology. Then we look for certain signs that are highly
> suggestive of certain diagnoses. Or we do a test that can be used to
> significantly reduce the possibility of certain conditions. In brief, this
> is what my algorithm is doing. We have identified about 50-60 relations
> between a symptom or sign or lab test and a diagnosis and try to apply it
> simultaneously. We believe that if the system can create dynamic check
> lists for any random combinations, it will improve the performance and
> consistency in decision making. If we can get structured studies like you
> mentioned that gives us precise numbers; we can plug that information into
> my algorithm to improve its performance. However, can we use the same
> number for different populations in a different demographic regions?
>
> My humble attempt with the algorithm is to solve a complex problem with a
> simple method. Like, catching a fly ball by keeping the angle to the ball
> constant rather than using calculus. But the option to use the numbers are
> kept open. However, we had only limited success when we used predictive
> analytics from a big database compared to current patho-physiologic
> algorithm.
>
> Vipin
>
>
>
> *Vipindas Chengat, MD FACP**  |  *Chairman, Physician Cognition, Inc.
>   —————————————————————————————————
>   Mobile: +1 (773) 575-3550
>   Email: Vipin at PhysicianCognition.Com <Vipin at PhysicianCognition.com>
>   Website: PhysicianCognition.Com <http://physiciancognition.com/>
>
>
>
> On Sun, Aug 2, 2015 at 4:59 PM, Mark H Ebell <ebell at uga.edu> wrote:
>
>> The question I”m asking is: “In patients presenting with <symptoms x>,
>> how accurate is <sign/symptom/combination> for the diagnosis of <disease
>> y>”. For example, “In patients with acute RTI, how accurate are fever,
>> cough, and combinations of symptoms for diagnosis of influenza? (or
>> pnuemonia?)”
>>
>> Not familiar with your database, but to answer these questions you need:
>>
>>    1. A moderately large group of patients with a clinically relevant
>>    spectrum of disease (I.e. Patients presenting to a primary care doc or ER
>>    with undifferentiated acute RTI)
>>    2. A prospective assessment of a range of signs and symptoms
>>    3. An accurate reference standard test (in this case PCR) given to
>>    all patients
>>
>> Clinical decision rules are typically developed using this kind of data
>> and using multivariate analysis to identify the optimal set of predictors.
>>
>> Best,
>>
>> Mark
>>
>> From: Vipindas Chengat
>> Date: Sunday, August 2, 2015 at 5:43 PM
>> To: Society to Improve Diagnosis in Medicine, Mark Ebell
>>
>> Subject: Re: [IMPROVEDX] Less life threatening differential diagnoses
>>
>> Very interesting post. Addressing sensitivity/specificity/ LR or
>> predictive values would pose another challenge. How would we calculate the
>> base rate? Is it just the prevalence of the population or the clinic's
>> population? How can we generalize those numbers? Mathematical strategy
>> using Bayesian might not be the perfect method; but looking for patterns
>> based on patho-physiological relations might be. That is how I built
>> physician cognition's decision algorithm and it is doing very well( I
>> think). It can even incorporate combined wisdom of professionals to
>> optimize the decision rules ( you can find it here
>> beta.physiciancognition.com).
>> Dr. Ebell, if you would like to conduct any research to optimize decision
>> pathways, I can provide it for free of cost. You can try any number of
>> symptoms, signs and labs in any combination and system will provide
>> differential diagnosis in the order of relevance, suggest further testing -
>> can be a clinical sign, symptom or lab and decision tree will move forward
>> based on answering those questions. You can also teach the system in real
>> time or it can learn from a big database. Please let me know what you
>> think. I think I have solved the very specific problem of combination of
>> symptoms. I believe that if there are any sub-optimal results, it is just a
>> matter of data and not the algorithm and can be solved within minutes.
>>
>>
>>
>> *Vipindas Chengat, MD FACP**  |  *Chairman, Physician Cognition, Inc.
>>   —————————————————————————————————
>>   Mobile: +1 (773) 575-3550
>>   Email: Vipin at PhysicianCognition.Com <Vipin at PhysicianCognition.com>
>>   Website: PhysicianCognition.Com <http://physiciancognition.com/>
>>
>>
>>
>> On Sun, Aug 2, 2015 at 4:08 PM, Mark H Ebell <ebell at uga.edu> wrote:
>>
>>> While very useful in many ways, that approach would not address
>>> sens/spec/LR, would not help with acute problems, and would not address
>>> combinations of symptoms, at least not easily
>>>
>>> Sent from Outlook
>>> <http://t.sidekickopen13.com/e1t/c/5/f18dQhb0S7lC8dDMPbW2n0x6l2B9nMJW7t5XZs5v_-llVcV_H264zw8vW653gwx56dBNpf9ks1lC02?t=http%3A%2F%2Ftaps.io%2Foutlookmobile&si=5919500165185536&pi=0c808af1-4c80-483f-b574-ba96e200f54f>
>>>
>>>
>>>
>>>
>>> On Sun, Aug 2, 2015 at 9:47 AM -0700, "Jochanan Benbassat" <
>>> benbasat at jdc.org> wrote:
>>>
>>> Unlike hospital based specialists, primary care physicians have the
>>> advantage of prolonged follow up of patients. Outpatient records offer the
>>> opportunity to determine the predictive value of abnormal syptoms and
>>> signs. In 1982 Dr Froom and I published in the BMJ the prevalence of
>>> microscopic hematuria in otherwise healthy male airpersonel aged 18-35 and
>>> the (negative) results of an average 7 years fillow up. I believe that a
>>> fsimilar ocus on the prevalence and outcomes of selected disease
>>> manifestations in the community after follow up offers an opportunity for
>>> such research
>>>
>>>
>>>
>>> Jochanan Benbassat MD
>>>
>>> Jerusaltm Israel
>>>
>>> ------------------------------
>>>
>>> *From:* Mark H Ebell [ebell at UGA.EDU]
>>> *Sent:* Sunday, August 02, 2015 16:21
>>> *To:* IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG
>>> *Subject:* Re: [IMPROVEDX] Less life threatening differential diagnoses
>>>
>>> Blow up NIH. Well ok, not literally. The average age at first RO1 is now
>>> 40, and less than 1% of funding goes to what one could generously call
>>> primary care research. And none to study of clinical diagnosis. PCORI even
>>> expressly forbids research to develop and validate clinical decision rules.
>>> This research is not expensive, but proper reference standards (PCR,
>>> imaging) cost money.
>>>
>>> Sent from Outlook
>>> <http://t.sidekickopen13.com/e1t/c/5/f18dQhb0S7lC8dDMPbW2n0x6l2B9nMJW7t5XZs5v_-llVcV_H264zw8vW653gwx56dBNpf9ks1lC02?t=http%3A%2F%2Ftaps.io%2Foutlookmobile&si=5919500165185536&pi=0c808af1-4c80-483f-b574-ba96e200f54f>
>>>
>>>
>>>
>>>
>>> On Sun, Aug 2, 2015 at 5:19 AM -0700, "Robert Bell" <
>>> rmsbell200 at yahoo.com> wrote:
>>>
>>> Excellent point. How to change things? What to do to get the funding?
>>>
>>> Rob Bell
>>>
>>> Sent from my iPad
>>>
>>> On Aug 1, 2015, at 8:58 PM, Mark H Ebell <ebell at UGA.EDU> wrote:
>>>
>>> As a primary care physician, we often see diseases early in their
>>> course, when signs and symptoms overlap with other conditions and
>>> biomarkers may be negative (think lupus). Unfortunately, there is no
>>> funding in the US to study clinical diagnosis in the primary care setting,
>>> at least not as long as NIH is dominated by basic scientists and sub
>>> specialists. That would be the only way to identify the truly useful signs
>>> and symptoms (or more likely combinations).
>>>
>>> Mark
>>>
>>>>>> Mark H. Ebell MD, MS
>>> Professor of Epidemiology University of Georgia
>>> Editor, *Essential Evidence* Deputy Editor, *American Family Physician*
>>> ebell at uga.edu
>>>
>>>
>>> From: Carmel Crock
>>> Reply-To: Society to Improve Diagnosis in Medicine, Carmel Crock
>>> Date: Saturday, August 1, 2015 at 9:55 PM
>>> To: " <IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG>
>>> IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG"
>>> Subject: Re: [IMPROVEDX] Less life threatening differential diagnoses
>>>
>>> Dear Rob
>>> I thought I would mention that at our Eye and ENT hospital emergency
>>> department, shingles is one of our commonest missed or delayed diagnosis,
>>> as patients present early with severe eye or ear pain but nothing (or
>>> little) to show on clinical examination.
>>> Regards
>>> Carmel Crock
>>> ------------------------------
>>> *From:* robert bell [
>>> <0000000296e45ec4-dmarc-request at LIST.IMPROVEDIAGNOSIS.ORG>
>>> 0000000296e45ec4-dmarc-request at LIST.IMPROVEDIAGNOSIS.ORG]
>>> *Sent:* Sunday, 2 August 2015 9:08 AM
>>> *To:* <IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG>
>>> IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG
>>> *Subject:* [IMPROVEDX] Less life threatening differential diagnoses
>>>
>>> To me it seems that despite frequency patterns medical students are
>>> rightly taught at great length to focus on not missing the life threatening
>>> diagnosis. Is this done at the expense of missing the diagnosis with less
>>> dangerous competing conditions that are on the differential diagnostic
>>> list.
>>>
>>> For example, how much do most medical students/residents know about
>>> shingles pain and symptoms prior to lesion development, with any lack of
>>> knowledge leading to the “diagnosis” of possible acute abdomen?
>>>
>>> I would argue that in training knowing FAR more about the less dangerous
>>> differential diagnoses would get us more quickly to an accurate diagnosis,
>>> at possibly lesser cost.
>>>
>>> So should there be in training more focus on the less serious competing
>>> differential diagnoses?
>>>
>>> Rob Bell
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>>
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>>
>>
>
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> Moderator:David Meyers, Board Member, Society for Improving Diagnosis in
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>
> To learn more about SIDM visit:
> http://www.improvediagnosis.org/
>
>






Moderator: David Meyers, Board Member, Society to Improve Diagnosis in Medicine


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