Difference between revisions of "Team:Sheffield/episode2"

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                            <h2>Firstly, why this project?</h2>
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                             <h2>What was our understanding at the start of our project?</h2>
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                            <p>From the beginning we were really enthusiastic about our project as we believed a device could have a large impact on the health of many. Our device, was focused on a general biomarker of bacterial infection to widen its application and make a bigger impact.</p>
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                             <p>At the start of the project our initial research focused on human antibiotic misprescription - the prescription of antibiotics where they will be of no benefit to the individual taking them. The US Center For Disease Control and Prevention (CDC), for example, reported that 1 in 3 courses of antibiotics in US for outpatients was unnecessary (Fleming-Dutra, et al., 2016). The review on antimicrobial resistance chaired by Lord O’Neill reported (2016) also found that 700,000 deaths were caused by drug-resistant strains of common bacterial infections, HIV, TB and malaria every year (O’Neill, 2016).</p>
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                             <h2>What was our understanding of the problem at the start of our project?</h2>
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                             <p>At the start of the project our initial research focused on human antibiotic misprescription (the prescription of antibiotics where they will be of no benefit to the individual taking them). The Center For Disease Control and Prevention, for example, reported that <span>1 in 3</span> prescriptions of antibiotics in US for outpatients was unnecessary. The review on antimicrobial resistance chaired by Lord O’Neil reported, in 2016, that <span>700,000</span> deaths were caused by drug-resistant strains of common bacterial infections, HIV, TB and malaria every year. This is a staggering number human lives with significant economic costs. We felt that tackling misprescription in order to reduce antibiotic wastage and therefore reduce development of antibiotic-resistant bacteria was key to relieving the problem of antibiotic-resistance in bacteria and the knock-on effects that this has.</p>
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<p>Reports like these and others really supported our decision to tackle antibiotic resistance from the point of antibiotic misprescription. Reducing unnecessary prescriptions through the use of our device would help maximise efficient usage and therefore minimise the rate of antibiotic resistance development.
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                            <p>We attended a patient panel at a local hospital specifically <span>The Research Advisory Panel for Infectious Diseases (RAPID)</span> which had a focus on infectious disease to get a more personal perspective of antibiotic usage. One member of the panel said that generally patients want a pill, especially if they feel ill and think that they need something to help them feel better. Another panel member said that her husband never finished a course of antibiotics - he would take them until he felt better and then would stop. If he then got ill again he would start taking the rest of the antibiotics, this was because he had a no waste attitude towards the antibiotics. </p>
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                          <p>From our discussions we perceived that understanding of the general public towards antibiotic use was lacking and that this was a driving force for misprescription as doctors felt under pressure to prescribe antibiotics in order to satisfy the patients. </p>
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                        <h2>What is our device trying to address?</h2>
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                                <h2>What was our device trying to address?</h2>
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                        <p>When we started our project we envisaged that our device would benefit GPs in determining which patients required antibiotics. We hoped that our device would impact on the antibiotic resistance problem by giving doctors, for the first time since the use of antibiotics began, a point of care device that gives an objective likelihood of a patient having a bacterial infection. This would give them greater confidence when prescribing antibiotics and also denying antibiotics to those who do not require them. Such that, it would be an important tool for decreasing antibiotic use, ultimately to slow the spread of antibiotic resistance.</p>
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                            <p>When we started our project we envisaged that we would create a point-of-care device that would benefit GPs in determining which patients required antibiotics.</p>
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                        <p>We created a flow diagram as an initial assessment of the decision making process that a GP goes through when presented with an individual potentially suffering a bacterial infection so that we could begin to work out where our decide would an impact.</p>
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                            <p>The device would detect a biomarker of bacterial infection giving an objective likelihood of a patient having a bacterial infection. This type of device would be the first of its kind, and would give doctors greater confidence when prescribing antibiotics, as well as denying antibiotics to those who do not require them. Ultimately, we hoped this tool would considerably alleviate the international issue of antibiotic-resistant bacteria.</p>
 +
                          <p>In order to breakdown the thought process that a GP goes through when deciding whether to prescribe antibiotics we created a flow diagram. We wanted to use this to determine where our device could have impact.</p>
 
                            
 
                            
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                         <p>As presented above, the decision process involves uncertainty, which is what we would like to reduce. </p>
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                         <p>Fig 2. Thought process a GP undergoes when making antibiotic prescription decision as hypothesised by our team.</p>
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                         <p>We then predicted where our device would influence the decision making of doctors.</p>
+
                        <p>The flow diagram above shows that a GP has to make a decision either to prescribe antibiotics as a precaution in cases where it is not clear if a patient has a bacterial infection or not from just the clinical symptoms. Doctors are experts at determining the nature of an infection however some bacterial and viral infections have very similar symptoms making it impossible to determine the exact nature of the infection on symptoms alone.</p>
 +
 
 +
                        <p>This uncertainty can currently only be addressed by taking a blood sample that is sent to a lab for testing. This may require cell culturing which can take up to a week or longer for example in the case of tuberculosis. A point-of-care device would target this uncertainty and make the process much more accurate.</p>
 +
 
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                         <p>This next flow diagram (below) predicted where our device would influence the decision making of doctors.</p>
 
                         <img src="https://static.igem.org/mediawiki/2016/7/77/T--Sheffield--P%2BP-simpleprocess-chart.png">
 
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                       <p>As shown above, what we would like to achieve is that we could make the prescription process simpler by providing clinicians data on the necessity of antibiotics.</p>
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                       <p>Fig 3. Input of our device into the antibiotic decision making process. Misprescription is avoided and patients requiring antibiotics get the treatment they require. K is the biomarker used in our device. The device will compare concentration of the biomarker in the blood sample (Blood [K]) with the concentration of biomarker expected in a non-bacterial infected blood sample (Baseline [K]) to determine the likelihood of a bacterial infection.
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                      <h3>References:</h3>
 +
 
 +
                      <p>Fleming-Dutra K.E., Hersh A.L., Shapiro D.J., et al., (2016). Prevalence of Inappropriate Antibiotic Prescriptions Among US Ambulatory Care Visits, 2010-2011. Cosgrove: Journal of the American Medical Association. 315(17):1864-1873.</p>
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                      <p>O'Neill, J., (2016). Tackling drug-resistant infections globally: final report and recommendations. London: Wellcome Trust & HM Government.</p>
 
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Revision as of 18:29, 15 October 2016

A template page

BRAINSTORMING

What was our understanding at the start of our project?

At the start of the project our initial research focused on human antibiotic misprescription - the prescription of antibiotics where they will be of no benefit to the individual taking them. The US Center For Disease Control and Prevention (CDC), for example, reported that 1 in 3 courses of antibiotics in US for outpatients was unnecessary (Fleming-Dutra, et al., 2016). The review on antimicrobial resistance chaired by Lord O’Neill reported (2016) also found that 700,000 deaths were caused by drug-resistant strains of common bacterial infections, HIV, TB and malaria every year (O’Neill, 2016).

Reports like these and others really supported our decision to tackle antibiotic resistance from the point of antibiotic misprescription. Reducing unnecessary prescriptions through the use of our device would help maximise efficient usage and therefore minimise the rate of antibiotic resistance development.

What was our device trying to address?

When we started our project we envisaged that we would create a point-of-care device that would benefit GPs in determining which patients required antibiotics.

The device would detect a biomarker of bacterial infection giving an objective likelihood of a patient having a bacterial infection. This type of device would be the first of its kind, and would give doctors greater confidence when prescribing antibiotics, as well as denying antibiotics to those who do not require them. Ultimately, we hoped this tool would considerably alleviate the international issue of antibiotic-resistant bacteria.

In order to breakdown the thought process that a GP goes through when deciding whether to prescribe antibiotics we created a flow diagram. We wanted to use this to determine where our device could have impact.

Fig 2. Thought process a GP undergoes when making antibiotic prescription decision as hypothesised by our team.

The flow diagram above shows that a GP has to make a decision either to prescribe antibiotics as a precaution in cases where it is not clear if a patient has a bacterial infection or not from just the clinical symptoms. Doctors are experts at determining the nature of an infection however some bacterial and viral infections have very similar symptoms making it impossible to determine the exact nature of the infection on symptoms alone.

This uncertainty can currently only be addressed by taking a blood sample that is sent to a lab for testing. This may require cell culturing which can take up to a week or longer for example in the case of tuberculosis. A point-of-care device would target this uncertainty and make the process much more accurate.

This next flow diagram (below) predicted where our device would influence the decision making of doctors.

Fig 3. Input of our device into the antibiotic decision making process. Misprescription is avoided and patients requiring antibiotics get the treatment they require. K is the biomarker used in our device. The device will compare concentration of the biomarker in the blood sample (Blood [K]) with the concentration of biomarker expected in a non-bacterial infected blood sample (Baseline [K]) to determine the likelihood of a bacterial infection.

References:

Fleming-Dutra K.E., Hersh A.L., Shapiro D.J., et al., (2016). Prevalence of Inappropriate Antibiotic Prescriptions Among US Ambulatory Care Visits, 2010-2011. Cosgrove: Journal of the American Medical Association. 315(17):1864-1873.

O'Neill, J., (2016). Tackling drug-resistant infections globally: final report and recommendations. London: Wellcome Trust & HM Government.