The Hidden Crisis in Infectious Disease Diagnostics: When Tests Fail to Identify the Causal Pathogen
The Hidden Crisis in Infectious Disease Diagnostics: When Tests Fail to Identify the Causal Pathogen
A 58-year-old patient arrives at the hospital with fever, shortness of breath, and a productive cough. A medical history includes diabetes and hypertension, making the patient vulnerable to severe infections. The clinical team suspects pneumonia and immediately orders a range of diagnostic tests, including blood cultures, sputum cultures, and molecular assays for common respiratory pathogens. However, all tests return negative, with no identifiable pathogen. Facing uncertainty, the doctors decide to administer broad-spectrum antibiotics to cover the most likely bacterial causes.
Despite five days of treatment, the patient shows no significant improvement. A second round of diagnostic tests is conducted, but the results remain inconclusive. As the condition deteriorates, a different combination of antibiotics is added, further expanding the treatment to cover additional bacteria. Eventually, the patient stabilizes, but the underlying cause of the infection remains unknown.
The Diagnostic Gap: 4 Reasons Why Current Tests Fail
Current diagnostic methods are often inadequate for identifying the causative agent in infectious diseases:
Limitations of Traditional Culture Methods
Traditional microbial culture techniques, often considered the “gold standard,” are slow and limited by the need for viable organisms. For many pathogens, especially fastidious bacteria, viruses, and fungi, culture methods lack the sensitivity required for detection. Studies have shown that only about 30% of bloodstream infections are confirmed with positive cultures, even in cases where an infection is clinically apparent.¹
Incomplete Pathogen Coverage in Molecular Assays
Molecular diagnostics, such as PCR-based methods, have enhanced the ability to detect specific pathogens quickly. However, these tests are inherently limited by their targeted design—they only identify pathogens for which primers are included in the assay. In cases where a patient is infected with a less common or unexpected pathogen, these tests yield negative results. Furthermore, emerging pathogens or variants can evade detection due to genetic mutations not covered by existing assays.²
Serological Testing and Its Constraints
Serological tests, which detect antibodies or antigens, are often used to diagnose viral infections. However, they have a lag time associated with the body’s immune response, reducing their utility in acute settings. Additionally, cross-reactivity with non-target organisms can lead to false positives, further complicating the diagnostic landscape.³
Diagnostic Bias and Overreliance on Syndromic Panels
The use of syndromic panels—molecular tests designed to detect a predefined set of pathogens associated with specific clinical syndromes—can lead to diagnostic bias. These panels are only as good as the pathogens included. In situations where the actual causative agent is not on the panel, the result will be negative, misleading clinicians to consider non-infectious causes or prescribe inappropriate treatments.
The Consequences of Infectious Disease Diagnostics Failure
When diagnostic tests fail to identify the causative pathogen, the consequences are significant. For the patient, this often means delays in receiving the correct treatment, prolonged illness, unnecessary exposure to broad-spectrum antibiotics, and an increased risk of complications or death. A meta-analysis in Clinical Infectious Diseases highlighted that patients with unidentified pathogens have a 30% higher mortality rate compared to those with a confirmed diagnosis⁴.
For healthcare systems, these diagnostic gaps translate to longer hospital stays, increased use of resources, and higher healthcare costs. The empirical use of broad-spectrum antibiotics not only drives up costs but also contributes to the growing crisis of antimicrobial resistance (AMR). A study published in JAMA noted that nearly 40% of antibiotic prescriptions in hospitals are unnecessary or inappropriate, largely due to the lack of definitive diagnostic information⁵.
The Path Forward: Toward More Accurate and Rapid Diagnostics
Addressing this crisis requires investment in better diagnostic tools that can provide rapid, comprehensive, and reliable results:
Metagenomic Next-Generation Sequencing (mNGS)
This method analyzes all nucleic acids present in a sample, theoretically enabling the detection of any pathogen, known or unknown, in a single test. Early studies have demonstrated its utility in identifying rare, novel, or atypical pathogens that traditional tests miss.⁶ However, mNGS is still in its early stages, requiring further development to reduce costs, increase speed, and address challenges related to data interpretation and contamination.
CRISPR-Based Diagnostics
Leveraging the precision of CRISPR technology, researchers are developing rapid diagnostic tools that can detect specific DNA or RNA sequences with high sensitivity and specificity. These tools hold potential for real-time pathogen detection directly at the point of care.⁷
Artificial Intelligence (AI) and Machine Learning
AI algorithms are being trained to analyze complex datasets, including electronic health records, imaging, and laboratory results, to predict the likelihood of specific infections. While still in the research phase, AI could potentially guide clinicians in choosing the right diagnostic tests and interpreting ambiguous results.
Conclusion
The hidden crisis in infectious disease diagnostics lies not only in the pathogens we know but also in those we fail to identify. As pathogens evolve and emerge, the limitations of traditional diagnostic methods become more apparent. Addressing this crisis demands a paradigm shift toward comprehensive, unbiased, and rapid diagnostic approaches that consider the full spectrum of potential pathogens. The development and integration of advanced diagnostic technologies such as mNGS, CRISPR-based tools, and AI-driven decision support are crucial for reducing uncertainty in managing infections, ensuring timely and accurate treatment, and ultimately protecting public health from the growing threat of antimicrobial resistance. Without these improvements, both patients and healthcare providers will continue to face significant challenges in the diagnosis and management of infectious diseases.
Meet us at ASM NGS 2024
By scheduling a meeting with us, you’ll gain insights into the science behind PaRTI-Seq, its validation data, and real-world applications. Ask questions and discuss potential collaborations that could drive your research and clinical initiatives forward. We look forward to connecting with you in Washington, D.C., and advancing the frontiers of microbiology together.
Schedule a MeetingReferences:
- Chiu, C. Y., & Miller, S. A. (2019). Clinical metagenomics. Nature Reviews Genetics, 20(6), 341-355.
- Gootenberg, J. S., Abudayyeh, O. O., Kellner, M. J., Joung, J., Collins, J. J., & Zhang, F. (2017). Multiplexed and portable nucleic acid detection platform with Cas13, Cas12a, and Csm6. Science, 360(6387), 439-444.
- Lee, C. C., et al. (2020). Clinical Accuracy of Blood Culture Methods. Journal of Clinical Microbiology.
- Rohde, H., et al. (2021). Challenges of Serological Testing for Infectious Diseases. Journal of Clinical Microbiology.
- Tamma, P. D., Avdic, E., & Li, D. X. (2017). Use of broad-spectrum antibiotics in hospitals: a critical issue. JAMA, 318(14), 1341-1342.
- Weinstein, M. P., & Patel, J. B. (2019). Unidentified Pathogens and Increased Mortality in Infectious Diseases. Clinical Infectious Diseases.
- Wilson, M. R., et al. (2014). Metagenomic Next-Generation Sequencing for Diagnosis of Infectious Diseases. New England Journal of Medicine.
