The medical community continues to strive for advancements in diagnostic technologies, particularly those that can detect pathogens directly from blood samples. A recent session at ASM Microbe 2024 in Atlanta chaired by Linoj Samuel delved into the complexities and challenges that have hindered the integration of these technologies into clinical practice. Direct-from-blood pathogen detection technologies are designed to bypass traditional culture methods, which can be time-consuming and sometimes ineffective in identifying fastidious or non-culturable pathogens. By utilizing such tools, healthcare providers can obtain actionable information swiftly, allowing for the narrowing of therapy and de-escalation of antibiotics. This rapid turnaround is crucial in managing sepsis, where every hour counts in the race against mortality and morbidity.
The session highlighted a blend of technical and non-technical challenges, from the intricacies of sample preparation, pathogen detection to the broader implications for clinical decision-making. Dr. Valeria Fabre’s insightful presentation underscored the potential of these technologies to revolutionize patient care, offering a clinician’s perspective on their impact on treatment strategies.
Economically, the implementation of these technologies presents both challenges and opportunities. While initial costs may be higher due to equipment and workforce training, the potential for reducing the length of hospital stays, decreasing the use of broad-spectrum antibiotics, and preventing the spread of resistant pathogens lead to significant savings.
Key takeaways from the discussion emphasized the need for a deeper understanding of the goals behind direct-from-blood pathogen detection. What are the specific outcomes we aim to achieve? How can these technologies influence clinical decisions, patient outcomes, and the economic aspects of healthcare? The current absence of this information hinders assessment of the value such diagnostics bring and thus their adoption. While much of the current efforts are focused on nucleic acid technologies, the development of imaging and spectroscopy-based technologies adds to the diversity of diagnostic approaches, potentially offering complementary benefits to nucleic acid-based methods. These technologies may provide additional layers of information, that may not be available through nucleic acid testing, such as greater confidence in detecting the presence/absence of bacteremia and antimicrobial susceptibility information.
Overall, there is a palpable sense of optimism about the future. The next generation of pathogen detection technologies promises to address current technical limitations more effectively. However, the adoption of these technologies hinges on a much better understanding, and more importantly demonstration, of their value. Failure to take this into account during development and design of validation studies may inhibit their use in clinical settings, which would be a shame.
Isolating bacteria directly from blood or positive blood culture present a unique set of problems for clinical microbiologists and researchers. We are happy that multiple recent studies using our Separation Cartridge have performed very well in both applications. This post relates to the positive blood culture application.
One ongoing study at a local hospital has observed that traditional ID results could be obtained within a day (whereas without using the cartridge results have taken 2-5 days) and that the ID results obtained using the cartridge matches that obtained by subculturing.
The shorter time-to-result using the cartridge was because it eliminated the need for subculturing decreasing the time to ID & AST by at least 24 hours. While it is generally accepted that that direct testing of positive blood culture broths is feasible, results have been variable (for instance better success with Gram-negative rods (GNR) than Gram-positive cocci (GPC)), workflow sub-optimal, or the method too expensive.
Preliminary experiences indicate that the cartridge does not have these limitations. The process takes ≤ 5 minutes, requires no new instrumentation, and uses one buffer that can be easily sourced. Results have been consistent regardless of whether it is GNR / GPC. More studies are taking place at other hospitals and microbiology labs that we will keep you updated on.
If this is an area of interest to you or your organization, please contact us (www.3idx.com). We are interested in setting up demos and additional studies to assess performance in different settings and applications. Thank you.
The Seventy-fifth World Health Assembly is being held in Geneva, Switzerland, from May 22-28, 2022. It is the first in-person Health Assembly since the start of the COVID-19 pandemic. On the occasion of the start of this assembly, many health-related organizations have released statements on healthcare priorities, inequities, and focus for the future.
Some of these observations relating to diagnostics caught our attention. We list four of them below and see them as further motivation for the work that we are doing at 3i Diagnostics.
The capacity to perform basic tests is available in just 1% of primary care clinics in low- and middle-income countries.
No diagnostic tests exist for 60% of the pathogens identified by the World Health Organization (WHO) as having the greatest outbreak potential. There are also no appropriate tests for half of the top 20 diseases responsible for the most lives lost.
Using COVID tests as an example, high-income countries use COVID tests at 10–100 times the rate of middle- and low-income countries. So, if tests are not inexpensive, testing is likely to be deficient.
Early diagnosis has been consistently linked to improved health outcomes and reduced out-of-pocket spending. However, diagnosis is the weakest link in healthcare systems globally.
One of the key learnings from COVID-19 is that investing in diagnostics will be central to rapid response to outbreaks and delivering appropriate care for infections. Deficiencies in testing affect not only people’s lives, but communities and economies, as COVID-19 clearly showed.
We have a first-hand experience, thanks to COVID, of when infections become deadly. Now imagine if treatments for diseases like salmonella, tuberculosis, malaria, and other infections are ineffective because of antimicrobial resistance (AMR). This would undo almost a century of medical progress.
AMR is when microbes adapt to the antimicrobial drugs used to treat them, rendering the drugs ineffective. Every time microbes are exposed to a drug, susceptible strains die in the presence of the antibiotic, whereas resistant strains survive and then multiply without competition from the susceptible strains. Antibiotic use is on the rise, with a 40% increase in use over 10 years (2000-2010). However, around 50% of antibiotics prescribed in the US are unnecessarily or inappropriately prescribed.
Why unnecessarily? Because it takes a long time to get test results, doctors prescribe antimicrobials while they wait. Since this is basically a trial-and-error process, they may end up trying several different antimicrobials by the time they get the diagnostic result. After they get the results, they may have to prescribe something entirely new. This process basically trains the microbes how to become resistant to antibiotics.
There are two ways to address AMR. The first is creating new antimicrobial drugs that the microbes are susceptible to. While this is an important way we can combat AMR, developing new drugs is reactive, rather than proactive. As we expose microbes to these new drugs, they will begin to develop resistance. This puts us back in the same place we started, and requires continual drug development to stay ahead. Even then, there is no guarantee that researchers will be able to develop a new drug by the time a microbe becomes resistant to the old one.
The second method of addressing AMR is developing better diagnostics. Better diagnostics will allow medical professionals to know what they’re dealing with faster, which allows them to use specific and effective treatments. Since microbes are being exposed to fewer drugs, they have less opportunities to become resistant, ultimately slowing down the spread of AMR. Doctors can continue using existing antimicrobials, and it gives researchers more time to develop new ones.
Patients with an antimicrobial resistant strain of infection can expect longer hospitalizations or stays in intensive care. They will also likely need more tests, more expensive treatments, and spend more time not working, which increases the financial impact of the infection. Additionally, major surgery and many cancer treatments will be more dangerous without effective treatments for an infection. Hospital visits will be more risky, as hospital-associated infections (HAIs) are often antimicrobial resistant.
AMR also has significant impacts at the global level. 50,000 people die every year just in Europe and the US because of AMR right now, and these impacts keep getting worse as time goes on. By 2050, some researchers estimate that AMR will cause 10 million deaths, which would be 1.8 million more deaths than cancer. Additionally, Gross Domestic Product (GDP) would be 2-3.5% lower and 100 trillion dollars would be lost.
Addressing AMR promptly and decisively is imperative to lessen these catastrophic impacts. The United States government, the World Health Organization, and other organizations have urged more careful use of antibiotics in healthcare and agriculture. They have also increased their support for the discovery and development of new antibiotics and better diagnostics. In the end, it will take the government, physicians, and all of us to effectively combat the spread of AMR. At the individual level, we need to increase awareness of AMR, and do our part to avoid pressuring physicians to prescribe antibiotics, especially when they are not needed.
There has been a notion among many in the medical community that a significant proportion of the morbidity and mortality associated with COVID-19 are due to secondary bacterial infections. This notion is, in part, attributed to studies from the 2009 H1N1 epidemic (Morris et al. ) , and early reports detailing increased presence of other respiratory pathogens in COVID-19 patients (Gerberding , Zhou et al. , Zhu et al. ). Accordingly treatment of COVID-19 patients have frequently included antibiotics.
As Andrew Jacobs reported in his New York Times article, physicians heavily prescribed antibiotics for treating these patients because of this concern. It now appears that this possibility is not as pervasive or as severe as initially thought (Rawson et al.).
While the fear of opportunistic infections have not come to pass, the overuse of antimicrobials in treating COVID-19 patients has highlighted concerns about catalyzing a slower-moving crisis namely antimicrobial resistance (AMR). Overuse of antibiotics is one of the factors that induces the development of resistance and its spread, which is precisely what we have done over these past few months.
What is interesting is that in both situations, COVID-19 and AMR, the immediate challenge has been our inability to identify those patients who need urgent medical attention. The challenges in testing subjects to determine if they are COVID-positive or not are well documented. Less well recognized is the situation in tackling AMR.
In the case of AMR, while much attention has been devoted to developing new drugs, as they should, the fact is that the fundamental problem is that we do not know which drug to administer to treat the patient efficiently and rapidly. That is, it is at heart a diagnostic problem. As the US Government Accountability Office succinctly explain in their assessment of US efforts to combat AMR “Without information to guide test usage, clinicians may not be able to select appropriate treatments for their patients.”
If you think that waiting for 48-72h to know if you were COVID-positive was unacceptable, why should it be for detecting bacterial infections, which could be just as, if not more, deadly (e.g. Sepsis)? [Today, it takes 1-5 days before the physician can learn if the patient has a bacterial infection or not] As Dr. Strich of the NIH clinical center is quoted as saying, “being prepared is more cost effective in the long run” and saves lives. “Antimicrobial resistance is a problem we cannot afford to ignore.”
And yet, there is not the same sense of urgency in developing diagnostics that can rapidly determine if a patient has a bacterial or vial infection let alone what the infection-causing pathogen is. Efforts to develop better diagnostics are not sufficiently supported by either the private or the public sectors.
We should all be asking ourselves why we are not pushing, with a greater sense of urgency, for better diagnostics that will be effective in combating AMR or the next pandemic instead of just hoping that the same approaches that have been tried for 20+ years with limited success will somehow suddenly provide the solution?
A common refrain in this post-antibiotic era is that we need new antibiotics and new diagnostics . While the challenges of developing a new antibiotic are better acknowledged and understood, many are very surprised that we still use fundamentally the same procedure as used pre-WWII.
So, how is it that we are, at the start of 2020 and ~30 years since the dawn of the PCR-era, still talking about the need for better bacterial diagnostics? There are multiple technical and real-world challenges that continue to stymie the development of PCR-based tests such as speed, volume that can be processed, number of bacteria identified, and so on. Sensitivity and Specificity of a PCR-based test (or rather the lack of sufficient Sensitivity and Specificity) are two key performance attributes that have held back widespread clinical use of PCR-based tests. For this discussion, we focus on identifying bacteria directly from blood for guiding treatment of bloodstream infections, especially those that might lead to severe sepsis or septic shock.
Multiple PCR-based approaches are being developed to rapidly identify bacteria from blood. To a neutral observer it would appear that the reason we do not have a suitable bacteria test is because we have not developed a good enough PCR-based test. And that suitably optimizing such a test would solve the problem. Is this correct? Or are there some fundamental limitations that have held back clinical application?
In our opinion, the fundamental technical limitation is centered around the sensitivity of PCR-based tests and a fundamental practical limitation is centered around the ability to lower costs to a level that the healthcare system can support.
There are numerous text books and reviews providing a basis for determining the sensitivity and specificity of a test. Here is one. Briefly, Sensitivity refers to how good a test is at correctly identifying people who have the disease. While Specificity is concerned with how good the test is at correctly identifying people who do not have the disease.
What can we learn from these numbers for a bacterial diagnostic based on PCR? Let’s take the case of a hospital that analyzes 100,000 bacterial ID tests a year.
The percentage of samples that turn positive upon blood culturing ranges from 5 to 10%. Using the upper end of this range it means that out of the 100,000 samples submitted for bacterial ID tests, ~10,000 turn positive. [Note: This is frequently viewed as the number of samples that actually contain bacteria though there is widespread acknowledgment that culturing underestimates the number. More on this later. But, for the moment, since culturing is the gold standard (albeit an imperfect one) let’s go with 10,000 samples out of the 100,000 samples contain bacteria and therefore represent an infection.]
Data from two commercially available PCR based tests exhibit sensitivity and specificity are shown in the table below.
Sensitivity
Specificity
Septifast ®
42.9%
88.2%
SepsiTest ®
28.6%
85.3%
The sensitivity of these two tests range from 28.6% to 42.9%. In other words, if the PCR result came back negative (suggesting there is no bacteria), you could only be ~43% sure that there really was no infection! Think about that for a moment. If you were a physician making this decision, would you decide not to administer antibiotics based on this result? You’re most likely going to administer the antibiotics as you’re not that confident that you can rely on the negative result. Similarly, the specificity of these two tests range from 85.3% to 88.2%. In this case, you can be 88% sure that if you got a positive result, the patient has an infection though there’s a 12% chance that the result may not be accurate.
Let’s apply the above numbers to our hospital that processes 100,000 blood culture samples. Suppose that these samples are tested by a PCR-based test instead of being submitted for blood culture testing. Using the Sensitivity and Specificity numbers from above, this means that, of the 100,000 samples, 15,400 will yield a positive result. But, only 4,600 of these are truly positive. So, you will end up administering antibiotics unnecessarily for a large number of patients based on the 10,800 positive results. Similarly, you would have had 84,600 negative results of which 5,400 are false negatives. This means that you would have chosen not to administer antibiotics despite patients needing it.
“True” Result
Positive
Negative
PCR test positive
4,600
10,800
PCR test negative
5,400
79,200
As a physician or a hospital, the number of incorrect decisions resulting by relying on such a test is too high – jeopardizing patient safety. Does it really provide a significant benefit over the current practice where antibiotics are administered based largely on clinical judgment? At the present moment at least, the general opinion is no. Since it does not offer significantly helpful guidance relative to current practice it does nothing to correct overuse or misuse of antibiotics.
Most of the time when we consider how to use the result from a diagnostic test, we ask ourselves, if it yields a positive result would I know what to do next? That is an important question. But, in this application, it is equally (if not more) important to ask if the test yields a negative result, would I know what to do next? There is not sufficient data (and may never be) to guide treatment decisions when a PCR-based test is negative. This is the fundamental technical limitation.
Besides their performance, PCR-based tests also create problems due to their cost and operation. A single test costs $70 – $200 based on the number of bacteria identified. Using our example, if such a test were used for each sample currently submitted for blood culture, it would cost each hospital $7-$20 million (just in consumables). Which consumes a significant portion of a microbiology lab budget leaving little to no money for other tests. And still leaves a large number of bacteria unidentified!
In theory one can design a PCR test that is multiplexed to cover a large number of bacteria. But, this will increase the cost per test. Splitting the number of bacteria identified across multiple test panels is one way of covering a broader range. But, this takes away the advantages of cost reduction due to large volumes. How does one respond to new strains or species that are of urgent concern that was not anticipated? In different regions of the world? The modifications to the manufacturing process to address these different demands make it very challenging for the manufacturer to keep costs low.
So, at a fundamental level, PCR-based tests for identifying bacteria directly from blood face limitations due to poor performance, high costs, and appear to not aid decision-making or operational efficiency.
Significantly improving sensitivity and controlling costs are therefore necessary, but not sufficient, conditions for enabling widespread use of PCR as a bacterial ID test direct from patient sample. And until they are satisfactorily resolved, there will continue to be a reluctance in using such tests to guide antibiotic treatment.
Which means that we owe it to ourselves and all patients to consider and develop alternative ID techniques. It’s not that one technique is a winner and the other the loser in such an effort. The problem is large enough that multiple solutions will be needed. The more diagnostic options we have, the better we can aid physicians in making the best decisions for treatment while slowing the spread of antimicrobial resistant bacteria.
