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United European Gastroenterology Journal logoLink to United European Gastroenterology Journal
. 2026 Aug 4;14(7):e70272. doi: 10.1002/ueg2.70272

Multiplex PCR to Diagnose Gastrointestinal Infections: Key Limitations in Interpretation

Giannoula S Tansarli 1, Ferric C Fang 1,2,✉
PMCID: PMC13435882  PMID: 42550030

ABSTRACT

Multiplex polymerase chain reaction (PCR) panels are increasingly used for the evaluation of acute diarrhea, providing rapid and sensitive detection of a broad range of enteric pathogens. However, their widespread adoption has created important interpretive challenges for clinicians. Positive results may reflect colonization, prolonged shedding, or organisms of uncertain pathogenicity rather than active infection, and current panels do not provide antimicrobial susceptibility or quantitative information. Incomplete pathogen coverage and false‐positive detections may further complicate result interpretation, particularly in patients with mild or self‐limited disease. Inappropriate test ordering or overinterpretation of results may lead to unnecessary antimicrobial therapy, delayed evaluation of non‐infectious causes of diarrhea, and increased healthcare utilization. This review summarizes the key limitations of multiplex GI PCR panels and provides a practical framework for integrating molecular results with clinical presentation, disease severity, and patient risk factors to support informed management decisions in everyday clinical practice.

Keywords: diarrhea, gastroenteritis, molecular diagnostics, multiplex PCR, PCR panels, syndromic testing

1. Introduction

Acute gastroenteritis remains one of the most common reasons for presentation to urgent care centers, outpatient clinics, and emergency departments [1, 2, 3]. Because clinical features are often nonspecific and overlap across infectious and non‐infectious etiologies, laboratory testing plays a central role in diagnostic evaluation, particularly in patients with severe disease, prolonged symptoms, or risk factors for complications [4, 5, 6].

The widespread adoption of syndromic multiplex polymerase chain reaction (PCR) panels has fundamentally altered the diagnostic approach to gastrointestinal (GI) infections [7]. By enabling the simultaneous molecular detection of multiple enteric pathogens from a single stool specimen, these assays have largely replaced conventional diagnostic strategies in many clinical settings. Their increasing use has been driven not only by technical advances in molecular diagnostics but also by operational pressures favoring rapid, comprehensive testing. A range of commercially available nucleic acid amplification test (NAAT) platforms are currently used in clinical laboratories for the diagnosis of gastrointestinal infections. These systems vary in target composition and include, among others, the BioFire FilmArray system [8], QIAstat‐Dx Gastrointestinal Panel [9], xTag Gastrointestinal Pathogen Panel [10], Verigene Enteric Pathogens Panel [11], BioCode Gastrointestinal Pathogen Panel [12], Seegene Allplex Gastrointestinal Panel [13], RIDAGENE Bacterial Stool Panel [14], EasyScreen Enteric Parasite Detection Kit [15], and enteric panels available for the BD MAX system [16, 17, 18, 19]; several of these assays are FDA‐cleared for clinical use in the United States, including the BioFire FilmArray GI Panel, xTAG GPP, and BD MAX enteric panels. The specific molecular targets and primer designs used by these assays are not always fully disclosed by manufacturers, which may limit independent assessment of assay performance and contribute to uncertainty when unexpected or discordant results occur.

However, the transition from traditional methods to highly sensitive (94.5%–100%) [8, 20, 21, 22] molecular panels has shifted the diagnostic challenge from pathogen detection to result interpretation. Molecular identification of enteric organisms does not necessarily imply causation, and positive results may reflect colonization, prolonged shedding, or organisms of uncertain pathogenicity rather than active infection [23]. In addition, multiplex PCR panels do not capture the full spectrum of infectious or non‐infectious causes of diarrhea nor provide ancillary information, such as antimicrobial susceptibility data or clonal typing.

As a result, the clinical impact of multiplex GI PCR testing is determined by how and when these assays are used and how their results are interpreted in the context of the patient's presentation and risk profile. Misinterpretation of multiplex GI PCR results may lead to unnecessary antimicrobial therapy, additional diagnostic testing, delayed evaluation of non‐infectious causes of diarrhea, and increased healthcare utilization. This review examines the key limitations in the interpretation of multiplex GI PCR panel results and discusses their implications for clinical decision‐making (Table 1).

TABLE 1.

Selected interpretive limitations common to multiplex GI PCR panels.

Limitation Example
Incomplete pathogen coverage Toxin‐mediated foodborne illness, less common pathogens
No antimicrobial susceptibility Shigella, Campylobacter
Lack of quantitative data Viral shedding versus infection
Colonization versus infection C. difficile, EPEC, EAEC
Detection of low‐pathogenicity organisms Y. enterocolitica 1A, E. dispar
Assay‐specific false positives Norovirus (selected platforms), Vibrio

2. Strengths of Multiplex GI PCR Panels

Multiplex GI PCR panels offer several well‐established advantages that have driven their widespread adoption in clinical practice. Compared with conventional stool culture, microscopy, and antigen‐based testing, these assays provide markedly higher analytic sensitivity, enabling more reliable detection of enteric pathogens, including organisms present at low abundance or that are difficult to recover by traditional methods [8, 16, 18, 24]. In addition, multiplex panels deliver rapid diagnostic results, with multiple studies showing that multiplex panels reduce diagnostic turnaround times from days to hours when compared with conventional stool culture, microscopy, and antigen‐based testing [25], as well as reduced utilization of other stool tests per patient [26]. The availability of rapid, organism‐specific results has also been associated with earlier initiation of antimicrobial therapy and a higher likelihood of targeted treatment rather than empiric therapy, highlighting an additional clinical benefit of multiplex testing [27]. In patients with inflammatory bowel disease (IBD), multiplex GI PCR panels are particularly valuable, as identification of an enteric pathogen has been shown to significantly influence management decisions; patients with detected infections are less likely to have IBD therapies initiated or escalated [28], and individuals with IBD are more likely than patients without IBD to have at least one enteric pathogen identified [3]. In this population, multiplex testing may be particularly helpful when patients present with acute worsening of diarrhea, as distinguishing infection from an inflammatory flare can be clinically challenging. Identification of an enteric pathogen may prompt a trial of targeted antimicrobial therapy prior to modification of immunosuppressive treatment, although results should be interpreted cautiously since detection of some organisms may represent colonization rather than the cause of symptoms. Another important strength of multiplex PCR testing is broad pathogen coverage [29] and improved detection of fastidious, slow‐growing, or historically underrecognized pathogens, such as diarrheagenic Escherichia coli and Plesiomonas shigelloides [8, 30, 31]. As a result, multiplex panels have expanded the recognized spectrum of causes of infectious diarrhea and reduced the number of cases previously labeled as idiopathic or gastroenteritis of unknown etiology.

Several studies have also highlighted the utility of multiplex panels in identifying enteric pathogens among populations at increased risk for sexually transmitted enteric infections, such as men who have sex with men (MSM) [27, 32, 33, 34]. In high‐income countries, multiplex PCR testing has additionally contributed to the identification of shigellosis outbreaks among individuals with limited access to hygiene, including persons experiencing homelessness (PEH), enabling faster implementation of treatment, infection control measures and community‐level interventions [35, 36]. Beyond individual patient care, multiplex GI PCR panels have also played an important role in outbreak detection and public health surveillance, including the unexpected recognition of outbreaks caused by Cyclospora cayetanensis and Cryptosporidium spp., which were previously identified only through acid‐fast staining of stool specimens [37, 38], as well as improved detection of Shigella outbreaks, facilitating earlier public health notification and intervention [34, 35, 39]. Finally, the ability of multiplex panels to simultaneously detect multiple pathogens has provided new insights into the epidemiology of mixed infections. In reported studies, coinfections have been detected in 16.4%–27.5% of tested specimens [20, 27, 29]. In a multicenter study by Spina et al., the most frequently observed combination was Campylobacter and enteropathogenic E. coli (EPEC), but triple infections with enteroaggregative E. coli (EAEC), EPEC, and enterotoxigenic E. coli (ETEC) were also reported. EPEC or EAEC was present in 84% of samples with multiple pathogens detected [29]. In clinical practice, detection of mixed bacterial or parasitic infections may influence management decisions and may require combination antimicrobial therapy [27]. Coinfections are now recognized to occur disproportionately in specific at‐risk groups, including MSM, travelers returning from low‐ and middle‐income countries, and PEH [27, 34, 40].

3. Self‐Limited Disease and Implications for Testing

Most episodes of acute infectious diarrhea are self‐limited and resolve with supportive care alone, particularly in otherwise healthy individuals. Consequently, multiplex GI PCR testing is not routinely indicated for all patients with acute diarrhea and is best reserved for those with severe or complicated illness (e.g., bloody diarrhea, systemic symptoms, or persistent disease) or those at increased risk for adverse outcomes, including immunocompromised patients and older adults [4, 6]. Inappropriate use of multiplex PCR panels in low‐risk patients increases the likelihood of detecting incidental or clinically irrelevant organisms, potentially leading to unnecessary treatment, additional testing, or patient concern.

4. Incomplete Pathogen Coverage

Despite their broad design, multiplex GI PCR panels do not capture the full spectrum of infectious causes of acute diarrhea. Important gaps in panel content remain, and awareness of these limitations is essential to avoid misinterpretation of negative results or missed diagnoses in selected clinical scenarios.

Several emerging or less commonly recognized bacterial pathogens are not included in most commercially available panels. These include some species of Aeromonas, non‐jejuni Campylobacter species, Providencia alcalifaciens, Escherichia albertii, Klebsiella oxytoca, and Laribacter hongkongensis [41, 42]. The strength of evidence supporting enteropathogenicity varies among these organisms. While E. albertii has been increasingly recognized as a diarrheal pathogen, the pathogenic potential of others, including certain Aeromonas species and K. oxytoca, may be context‐dependent. Yersinia pseudotuberculosis is an established enteric pathogen that can present with diarrhea, mesenteric lymphadenitis and pseudo‐appendicitis, but is not detected by most multiplex panels [43]. Although individually uncommon, these organisms have been increasingly implicated in diarrheal illness and may be clinically relevant in patients with compatible exposures or epidemiologic risk factors [41, 42]. Their detection continues to rely on targeted culture‐based methods or specialized molecular assays [41].

Coverage limitations also extend to region‐specific pathogens, particularly parasitic organisms endemic in certain geographic areas. With the exception of Giardia, Entamoeba histolytica, Cryptosporidium, and Cyclospora, most parasitic causes of diarrhea—including microsporidia, Strongyloides, and Ascaris—are not detected by multiplex PCR panels [44]. In patients with a relevant travel history, chronic symptoms, or eosinophilia, conventional ova and parasite (O&P) examination remains an essential diagnostic tool [44, 45].

Multiplex PCR panels also fail to identify several important causes of foodborne illness. Pathogens such as Listeria monocytogenes and toxin‐mediated illnesses caused by Staphylococcus aureus, Bacillus cereus, and Clostridium perfringens are not detected by these assays and account for a substantial proportion of acute gastrointestinal disease [46, 47]. Diagnosis of these conditions should be guided by clinical and exposure history and typically requires specialized testing performed in public health or reference laboratories, often involving demonstration of toxin production or detection of the toxin itself rather than identification of the organism alone.

A related interpretive challenge is the potential over‐reliance on a negative multiplex PCR result in evidence against an infectious etiology. Given the pathogens not included in current panels, a negative result should not be equated with the absence of infection when clinical suspicion remains high, and additional diagnostic evaluation may be warranted.

5. Lack of Antimicrobial Susceptibility Information

A major limitation of multiplex GI PCR panels is the absence of phenotypic antimicrobial susceptibility information. While these assays provide rapid organism identification, they do not offer data on antimicrobial resistance, which remains critical for guiding therapy in selected cases of bacterial gastroenteritis and for supporting public health surveillance.

In contrast to multiplex PCR panels used for bloodstream infections or pneumonia, GI panels do not include targets for antimicrobial resistance genes. The lack of susceptibility information may limit their role in definitive treatment selection, particularly in infections where resistance to commonly used agents is prevalent. Rising resistance to macrolides and fluoroquinolones among Shigella and Campylobacter isolates has been reported in several geographic regions, particularly in travelers or in men who have sex with men, making empiric therapy increasingly unreliable in some settings [33, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61]; in such cases, clinicians may be forced to base treatment decisions on local epidemiology in the absence of susceptibility results.

The lack of resistance data has additional implications in the context of sexually transmitted enteric infections, such as shigellosis. In these cases, administration of ineffective antimicrobial therapy may prolong bacterial shedding and facilitate ongoing transmission, with consequences extending beyond the individual patient to the community level. This concern is amplified when organisms detected by PCR fail to grow in culture, precluding subsequent susceptibility testing and limiting opportunities for public health intervention and strain typing to support outbreak investigation.

Together, these considerations underscore the continued importance of reflexive culture and targeted susceptibility testing following positive multiplex PCR results. While molecular panels have streamlined pathogen detection, they cannot replace culture‐based methods for resistance determination, surveillance, and epidemiologic studies. Integrating multiplex PCR testing with complementary diagnostic approaches remains essential for informed clinical management and public health response.

6. Lack of Quantitative Information

Most multiplex GI PCR panels generate qualitative results that report the presence or absence of specific pathogens without providing information on organism burden. The absence of quantitative data makes it difficult to distinguish low‐level carriage from clinically meaningful infection. This challenge is particularly relevant for organisms that may be present in asymptomatic individuals or shed for prolonged periods following symptom resolution.

In other areas of infectious diseases, quantitative measures—such as viral load in HIV, hepatitis B, or cytomegalovirus infection—play a central role in diagnosis, risk stratification, and treatment monitoring. In contrast, multiplex GI PCR panels do not currently provide analogous metrics that could help to contextualize positive results. Cycle threshold (Ct) or crossing point (Cp) values, which might serve as a surrogate measure of organism burden, are not reported to clinicians and lack standardized interpretive thresholds across platforms, although some assays generate such parameters as part of their analytical output, which may occasionally assist in the evaluation of results that do not correspond to the clinical presentation [62]. A previous study showed that higher Ct values on real‐time PCR were significantly lower in cases than in controls for some enteric bacterial pathogens [63], while another study found that the incidence of some bacterial causes of diarrhea was higher when tested by qPCR compared to other non‐quantitative assays [64].

The lack of quantitative information therefore limits the ability of multiplex GI PCR testing to inform clinical decision‐making beyond pathogen identification. Future incorporation of standardized quantitative or semi‐quantitative reporting may help improve discrimination between colonization and active infection, at least for certain pathogens; however, until such approaches are validated, quantitative results must be interpreted cautiously and in conjunction with the clinical presentation.

7. Distinguishing Colonization From Infection

The high analytic sensitivity of multiplex GI PCR panels is a major strength but necessitates a clinical context to distinguish colonization from active infection. Because PCR assays detect microbial nucleic acids rather than viable organisms or toxin production, they cannot reliably differentiate between true infection and colonization.

This challenge is well illustrated by Clostridioides difficile, a well‐recognized example of the inability of laboratory testing to distinguish colonization from disease in which asymptomatic colonization is common, particularly among hospitalized patients and long‐term care residents [65, 66]. Molecular assays, including those used in multiplex PCR panels, detect genes encoding toxins A and B (e.g., tcdA and tcdB), rather than the toxin itself; a positive result may reflect either C. difficile infection (CDI) or colonization with toxigenic C. difficile. PCR positivity alone therefore does not establish disease in the absence of appropriate clinical correlation. Although NAAT is the most sensitive laboratory method for detecting toxigenic C. difficile [67], accurate diagnosis of CDI requires integration of laboratory results with the clinical presentation [68]. Current diagnostic guidelines differ somewhat in their emphasis on toxin detection: European guidance (ESCMID/ECDC) recommends multistep algorithms incorporating toxin assays [69], whereas North American guidance (IDSA/SHEA) allows NAAT‐based strategies in settings with appropriate diagnostic stewardship [70]. Similar interpretive challenges arise in immunocompromised populations, such as hematopoietic stem cell transplant recipients, in whom diarrhea frequently results from non‐infectious causes including conditioning regimens, graft‐versus‐host disease, or medication effects [71]. In these patients, the differential diagnosis is broad and may also include opportunistic infections not detected by standard multiplex panels, such as cytomegalovirus colitis, microsporidiosis, or other parasitic infections, further underscoring the importance of integrating molecular results with clinical context.

Interpretive uncertainty also applies to several diarrheagenic E. coli pathotypes detected by some multiplex PCR panels. EPEC and EAEC are commonly identified in both symptomatic and asymptomatic individuals, particularly in otherwise healthy adults, complicating attribution of causality when detected in isolation [72, 73]. However, published evidence and anecdotal reports suggest that EPEC and EAEC can cause persistent diarrhea in both children and adults, including in high‐income countries [72, 74]. In these cases, careful integration of clinical features (i.e., duration of symptoms), host factors, and epidemiologic context can help to avoid overdiagnosis and unnecessary treatment.

8. Organisms of Uncertain or Low Pathogenicity

Multiplex GI PCR panels may detect organisms whose clinical relevance is uncertain or inherently low, creating additional challenges for result interpretation. Examples include Yersinia enterocolitica biotype 1A and Entamoeba dispar. Y. enterocolitica biotype 1A lacks key virulence determinants found in pathogenic Y. enterocolitica strains, including the virulence plasmid (pYV) and associated genes required for epithelial invasion and toxin production [75]. Because molecular assays detect targets that are not directly linked to these virulence determinants, positive PCR results cannot distinguish Y. enterocolitica biotypes. Biotype 1 A is generally regarded as nonpathogenic or of minimal pathogenic potential despite its inclusion as a reportable target on some multiplex PCR panels. Detection of this organism may therefore represent transient colonization or incidental carriage rather than the cause of clinical disease.

Similarly, although multiplex PCR panels are designed to detect Entamoeba histolytica, assay cross‐reactivity with the closely related nonpathogenic species Entamoeba dispar has been reported, particularly when E. dispar is present at higher concentrations [76]. E. dispar has been described as an intestinal colonizer, including among MSM in which enteric protozoa may be detected in the absence of invasive disease [77]. In such patients, molecular detection of E. histolytica without a compatible clinical presentation may reflect E. dispar colonization or non‐invasive infection rather than true amebiasis [77]. These findings underscore the importance of distinguishing pathogenic E. histolytica from non‐pathogenic Entamoeba species when interpreting molecular test results. More broadly, the detection of organisms with low or uncertain pathogenic potential should be interpreted cautiously and correlated with the clinical presentation and epidemiologic context before attributing symptoms to the identified organism.

9. Hybrid and Overlapping Pathotypes in Diarrheagenic E. coli

Diarrheagenic Escherichia coli are traditionally classified into six major pathotypes based on the presence of specific virulence determinants: enterotoxigenic E. coli (ETEC), enteropathogenic E. coli (EPEC), Shiga toxin–producing E. coli (STEC), enteroinvasive E. coli (EIEC), enteroaggregative E. coli (EAEC), and diffusely adherent E. coli (DAEC) [78]. Commercial multiplex GI PCR panels detect selected virulence genes associated with several diarrheagenic E. coli pathotypes (e.g., STEC, ETEC, EPEC, EAEC, and EIEC), but no currently available panel targets all recognized pathotypes, and DAEC is generally not included. Although STEC, ETEC, and EIEC are well‐established causes of diarrheal disease, the clinical significance of other pathotypes—particularly EAEC, DAEC, and some EPEC strains—remains less certain, as these organisms are frequently detected in asymptomatic individuals.

The increasing recognition of hybrid diarrheagenic E. coli strains highlights an important interpretive limitation of multiplex GI PCR panels. These assays detect individual virulence genes used to define traditional E. coli pathotypes rather than complete strains or functional pathogenicity. Consequently, organisms harboring virulence determinants from multiple pathotypes, such as EAEC and EPEC, may be reported as overlapping detections though the clinical relevance of such hybrids remains incompletely understood.

Hybrid strains driven by combinations involving Shiga toxin (e.g., EPEC/STEC or EAEC/STEC hybrids carrying stx) have been implicated in severe cases of diarrhea, including E. coli O157:H7 and the German outbreak serotype E. coli O104:H4 that are frequently complicated by hemolytic‐uremic syndrome [79, 80]. Furthermore, hybrid EPEC/EAEC strains causing acute diarrhea have been reported in Brazil, but information regarding the impact on illness severity is not available [81]. Because multiplex PCR testing does not assess virulence gene expression, toxin production, invasiveness, or organism burden, distinguishing clinically meaningful infection from incidental detection remains challenging.

10. False‐Positive Detections

In addition to the general interpretive challenges discussed above, several assay‐ or target‐specific limitations have been reported for particular multiplex GI PCR platforms. False‐positive detections have been reported for selected targets on multiplex GI PCR panels, most notably for the norovirus assay on the BioFire FilmArray GI Panel [82], prompting both institutional mitigation strategies, through confirmatory testing using alternative singleplex molecular assays, and regulatory review. Manufacturer‐initiated post‐marketing performance follow‐up studies demonstrated preserved clinical sensitivity but reduced specificity compared to the original studies (negative percent agreement 96.5% vs. 98.8%) [83], reinforcing concerns regarding analytic false positivity and supporting recommendations for confirmatory testing when results are discordant with the clinical presentation or outside the usual seasonal incidence.

In parallel, it is important to recognize that not all apparent false‐positive norovirus results reflect assay failure. Prolonged viral shedding represents a major contributor to clinically misleading PCR positivity. Norovirus RNA may remain detectable in stool for weeks after symptom resolution, particularly in young children, older adults, and immunocompromised individuals [84, 85, 86]. In addition, norovirus can be detected in asymptomatic individuals [87], further complicating interpretation in patients with alternative explanations for diarrhea. In these settings, a positive PCR result may reflect prior or incidental infection rather than the cause of current symptoms.

Similar interpretive challenges have been described for Campylobacter. In a recent study, the implementation of the BioFire FilmArray GI Panel was associated with an increase in Campylobacter detections that were not confirmed by stool culture (culture confirmation occurred in 62% of BioFire detections, compared with 78% of detections using other culture‐independent methods, p < 0.05), prompting analysis of melt curve data [88]. Specimens with PCR‐positive/culture‐negative results frequently exhibited atypical melt curve patterns compared with PCR‐positive/culture‐positive samples, leading to the suggestion that some detections may represent false positives. However, it is also possible that some atypical melt curves reflect amplification of variant Campylobacter sequences that differ from the reference strains used to define standard melt curve signatures, and some culture‐negative cases may represent fastidious strains not culturable on selective media. Of note, a recent study found irregular amplification curves on the BD MAX Extended Enteric Bacterial Panel that were not confirmed by culture for Vibrio spp. and Yersinia enterocolitica [89], while another study on the BD MAX Enteric Bacterial Panel showed that Campylobacter spp. detections that were not confirmed by culture had higher Ct values than confirmed ones [90]. Some false‐positive Vibrio detections may result from DNA contamination of holding media, which includes agar as a component [91]. Because the multiplex assay detects Vibrio spp. at the genus level, these detections cannot be attributed to specific pathogenic Vibrio species. Further research is needed to distinguish which atypical curves represent analytic false‐positive detections and which reflect true molecular identification of genetically divergent or fastidious bacterial strains.

11. Strategies to Improve Interpretation and Clinical Use

Optimizing the clinical impact of multiplex GI PCR panels requires a diagnostic stewardship approach that addresses both appropriate test utilization and thoughtful result interpretation. A proposed algorithm for the interpretation of multiplex GI PCR panel results is shown in Figure 1. Table 2 summarizes practical considerations for clinicians interpreting multiplex GI PCR results, including guidance on appropriate test ordering, interpretation of positive and negative findings, use of complementary diagnostic testing, and the role of diagnostic stewardship. Testing should be targeted to clinical scenarios in which results are likely to influence management and interpreted in the context of patient presentation and epidemiologic risk. At the same time, syndrome‐based multiplex testing strategies may identify unexpected pathogens that would not otherwise be considered on clinical grounds alone, including community‐acquired Clostridioides difficile infection. These approaches may therefore contribute not only to individual patient management but also to improved detection of atypical or emerging pathogens and to a better understanding of the epidemiology of enteric infections. Figure 2 highlights patient populations and clinical scenarios in which multiplex GI PCR testing is most likely to affect clinical decision‐making.

FIGURE 1.

FIGURE 1

Proposed algorithm for the interpretation of multiplex GI PCR panels. Created with BioRender.com.

TABLE 2.

Practical tips for gastroenterologists: Interpreting multiplex GI PCR panel results.

Order testing selectively

Reserve multiplex GI PCR panels for patients with severe, persistent, or bloody diarrhea, systemic illness, immunocompromised status, or public health concerns; avoid routine testing in mild, self‐limited diarrhea.

Interpret positive results in clinical context

PCR detects microbial nucleic acids rather than viable organisms or toxin; positive results may reflect colonization, prolonged shedding, or organisms of uncertain pathogenicity.

Do not equate a negative panel with absence of infection

Multiplex panels do not detect all enteric pathogens (e.g., toxin‐mediated foodborne illness, some parasites); further evaluation may be warranted when clinical suspicion remains high.

Use complementary testing when indicated

Consider reflex stool culture for susceptibility testing and public health surveillance in patients with bacterial gastroenteritis, and ova and parasite examination in patients with relevant travel or exposure history.

Collaborate and steward diagnostic resources

Engage the microbiology laboratory or infectious diseases specialists for discordant or complex results and apply diagnostic stewardship principles to minimize overdiagnosis and unnecessary treatment.

FIGURE 2.

FIGURE 2

When to use multiplex GI PCR testing. Created with BioRender.com.

Reflex testing algorithms remain an important adjunct to molecular diagnostics. For selected bacterial pathogens, follow‐up stool culture enables antimicrobial susceptibility testing, strain characterization, and public health surveillance, helping to offset key limitations of PCR‐based assays. Close collaboration among infectious diseases specialists, gastroenterologists, and the microbiology laboratory further supports consistent test ordering practices, meaningful result reporting, and interpretation of complex or ambiguous findings.

12. Conclusions

Multiplex PCR panels have become a cornerstone of gastrointestinal infection diagnostics, providing rapid and sensitive detection of a broad range of enteric pathogens. However, their high analytic sensitivity and wide scope introduce interpretive challenges, including incomplete pathogen coverage, absence of antimicrobial susceptibility data, detection of colonization or low‐pathogenicity organisms, and lack of quantitative information. Some of these challenges are inherent to multiplex molecular testing in general, whereas others reflect assay‐ or target‐specific limitations observed with particular diagnostic platforms.

Clinical judgment remains central to the effective use of these assays. Thoughtful test selection, integration of molecular results with a clinical context, and application of diagnostic stewardship principles are essential to maximizing benefit. Recognizing these limitations allows clinicians to use multiplex GI PCR results more effectively to guide management and avoid unnecessary interventions across clinical settings.

Conflicts of Interest

GST and FCF did not receive payment for their work on this manuscript. GST (AI182462) and FCF (AI150041, AI160130) are recipients of support from the National Institutes of Health. FCF has been a paid consultant for bioMérieux and Abbott Diagnostics.

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

References

  • 1. DuPont H. L., “Clinical Practice. Bacterial Diarrhea,” New England Journal of Medicine 361 (2009): 1560–1569, 10.1056/NEJMcp0904162. [DOI] [PubMed] [Google Scholar]
  • 2. Bresee J. S., Marcus R., Venezia R. A., et al., “The Etiology of Severe Acute Gastroenteritis Among Adults Visiting Emergency Departments in the United States,” Journal of Infectious Diseases 205, no. 9 (2012): 1374–1381, 10.1093/infdis/jis206. [DOI] [PubMed] [Google Scholar]
  • 3. Moon R. C., Bleak T. C., Rosenthal N. A., et al., “Epidemiology and Economic Burden of Acute Infectious Gastroenteritis Among Adults Treated in Outpatient Settings in US Health Systems,” American Journal of Gastroenterology 118, no. 6 (2023): 1069–1079, 10.14309/ajg.0000000000002186. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Hatchette T. F. and Farina D., “Infectious Diarrhea: When to Test and When to Treat,” Canadian Medical Association Journal 183, no. 3 (2011): 339–344, 10.1503/cmaj.091495. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Riddle M. S., DuPont H. L., and Connor B. A., “ACG Clinical Guideline: Diagnosis, Treatment, and Prevention of Acute Diarrheal Infections in Adults,” American Journal of Gastroenterology 111, no. 5 (2016): 602–622, 10.1038/ajg.2016.126. [DOI] [PubMed] [Google Scholar]
  • 6. Shane A. L., Mody R. K., Crump J. A., et al., “2017 Infectious Diseases Society of America Clinical Practice Guidelines for the Diagnosis and Management of Infectious Diarrhea,” Clinical Infectious Diseases 65, no. 12 (2017): e45–e80, 10.1093/cid/cix959. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. Ramanan P., Bryson A. L., Binnicker M. J., Pritt B. S., and Patel R., “Syndromic Panel‐Based Testing in Clinical Microbiology,” Clinical Microbiology Reviews 31, no. 1 (2018): e00024‐17, 10.1128/cmr.00024-17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Buss S. N., Leber A., Chapin K., et al., “Multicenter Evaluation of the Biofire FilmArray Gastrointestinal Panel for Etiologic Diagnosis of Infectious Gastroenteritis,” Journal of Clinical Microbiology 53, no. 3 (2015): 915–925, 10.1128/jcm.02674-14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Boers S. A., Peters C. J. A., Wessels E., Melchers W. J. G., and Claas E. C. J., “Performance of the QIAstat‐Dx Gastrointestinal Panel for Diagnosing Infectious Gastroenteritis,” Journal of Clinical Microbiology 58, no. 3 (2020): e01793‐19, 10.1128/jcm.01737-19. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10. Navidad J. F., Griswold D. J., Gradus M. S., and Bhattacharyya S., “Evaluation of Luminex xTAG Gastrointestinal Pathogen Analyte‐Specific Reagents for High‐Throughput, Simultaneous Detection of Bacteria, Viruses, and Parasites of Clinical and Public Health Importance,” Journal of Clinical Microbiology 51, no. 9 (2013): 3018–3024, 10.1128/jcm.00896-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Beckman A. K. and Ferrieri P., “Prospective Investigation of an Automated PCR/Nucleic Acid Microarray‐based Platform for Enteric Pathogen Testing,” Laboratory Medicine 50, no. 4 (2019): 390–395, 10.1093/labmed/lmz022. [DOI] [PubMed] [Google Scholar]
  • 12. Knoth C., Humphries R., Johnson J. K., et al., “Multicenter Evaluation of BioCode GPP for Syndromic Molecular Detection of Gastrointestinal Pathogens From Stool Specimens,” Journal of Clinical Microbiology 62, no. 3 (2024): e0154523, 10.1128/jcm.01545-23. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13. Yoo J., Park J., Lee H. K., et al., “Comparative Evaluation of Seegene Allplex Gastrointestinal, Luminex xTAG Gastrointestinal Pathogen Panel, and BD MAX Enteric Assays for Detection of Gastrointestinal Pathogens in Clinical Stool Specimens,” Archives of Pathology & Laboratory Medicine 143, no. 8 (2019): 999–1005, 10.5858/arpa.2018-0002-oa. [DOI] [PubMed] [Google Scholar]
  • 14. Berenger B. M., Chui L., Ferrato C., Lloyd T., Li V., and Pillai D. R., “Performance of Four Commercial Real‐Time PCR Assays for the Detection of Bacterial Enteric Pathogens in Clinical Samples,” International Journal of Infectious Diseases 114 (2022): 195–201, 10.1016/j.ijid.2021.10.035. [DOI] [PubMed] [Google Scholar]
  • 15. Stark D., Roberts T., Ellis J. T., Marriott D., and Harkness J., “Evaluation of the EasyScreen Enteric Parasite Detection Kit for the Detection of Blastocystis spp., Cryptosporidium spp., Dientamoeba Fragilis, Entamoeba Complex, and Giardia intestinalis From Clinical Stool Samples,” Diagnostic Microbiology and Infectious Disease 78, no. 2 (2014): 149–152, 10.1016/j.diagmicrobio.2013.10.013. [DOI] [PubMed] [Google Scholar]
  • 16. Harrington S. M., Buchan B. W., Doern C., et al., “Multicenter Evaluation of the BD Max Enteric Bacterial Panel PCR Assay for Rapid Detection of Salmonella spp., Shigella spp., Campylobacter spp. (C. Jejuni and C. Coli), and Shiga Toxin 1 and 2 Genes,” Journal of Clinical Microbiology 53, no. 5 (2015): 1639–1647, 10.1128/jcm.03480-14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17. Madison‐Antenucci S., Relich R. F., Doyle L., et al., “Multicenter Evaluation of BD Max Enteric Parasite Real‐Time PCR Assay for Detection of Giardia Duodenalis, Cryptosporidium Hominis, Cryptosporidium Parvum, and Entamoeba Histolytica ,” Journal of Clinical Microbiology 54, no. 11 (2016): 2681–2688, 10.1128/jcm.00765-16. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Simner P. J., Oethinger M., Stellrecht K. A., et al., “Multisite Evaluation of the BD Max Extended Enteric Bacterial Panel for Detection of Yersinia Enterocolitica, Enterotoxigenic Escherichia Coli, Vibrio, and Plesiomonas Shigelloides From Stool Specimens,” Journal of Clinical Microbiology 55, no. 11 (2017): 3258–3266, 10.1128/jcm.00911-17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Stokes W., Simner P. J., Mortensen J., et al., “Multicenter Clinical Validation of the Molecular BD Max Enteric Viral Panel for Detection of Enteric Pathogens,” Journal of Clinical Microbiology 57, no. 9 (2019): e00306–e00319, 10.1128/jcm.00306-19. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20. Khare R., Espy M. J., Cebelinski E., et al., “Comparative Evaluation of Two Commercial Multiplex Panels for Detection of Gastrointestinal Pathogens by Use of Clinical Stool Specimens,” Journal of Clinical Microbiology 52, no. 10 (2014): 3667–3673, 10.1128/jcm.01637-14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Huang R. S., Johnson C. L., Pritchard L., Hepler R., Ton T. T., and Dunn J. J., “Performance of the Verigene(R) Enteric Pathogens Test, Biofire FilmArray Gastrointestinal Panel and Luminex xTAG(R) Gastrointestinal Pathogen Panel for Detection of Common Enteric Pathogens,” Diagnostic Microbiology and Infectious Disease 86, no. 4 (2016): 336–339, 10.1016/j.diagmicrobio.2016.09.013. [DOI] [PubMed] [Google Scholar]
  • 22. Chhabra P., Gregoricus N., Weinberg G. A., et al., “Comparison of Three Multiplex Gastrointestinal Platforms for the Detection of Gastroenteritis Viruses,” Journal of Clinical Virology 95 (2017): 66–71, 10.1016/j.jcv.2017.08.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Messacar K., Parker S. K., Todd J. K., and Dominguez S. R., “Implementation of Rapid Molecular Infectious Disease Diagnostics: The Role of Diagnostic and Antimicrobial Stewardship,” Journal of Clinical Microbiology 55, no. 3 (2017): 715–723, 10.1128/jcm.02264-16. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Szymczak W. A., Engsbro A. L., Lisby J. G., et al., “Multicenter Evaluation of the QIAstat‐Dx Gastrointestinal Panel 2, a Multiplex PCR Platform for the Diagnosis of Acute Gastroenteritis,” Journal of Clinical Microbiology 63, no. 8 (2025): e0198324, 10.1128/jcm.01983-24. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Sobczyk J., Jain S., Sun X., et al., “Comparison of Multiplex Gastrointestinal Pathogen Panel and Conventional Stool Testing for Evaluation of Patients With HIV Infection,” Open Forum Infectious Diseases 7, no. 1 (2020): ofz547, 10.1093/ofid/ofz547. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26. Moon R. C., Bleak T. C., Rosenthal N. A., et al., “Relationship Between Diagnostic Method and Pathogen Detection, Healthcare Resource Use, and Cost in U.S. Adult Outpatients Treated for Acute Infectious Gastroenteritis,” Journal of Clinical Microbiology 61, no. 2 (2023): e0162822, 10.1128/jcm.01628-22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Cybulski R. J. Jr., Bateman A. C., Bourassa L., et al., “Clinical Impact of a Multiplex Gastrointestinal Polymerase Chain Reaction Panel in Patients With Acute Gastroenteritis,” Clinical Infectious Diseases 67, no. 11 (2018): 1688–1696, 10.1093/cid/ciy357. [DOI] [PubMed] [Google Scholar]
  • 28. Axelrad J. E., Joelson A., Green P. H. R., et al., “Enteric Infections Are Common in Patients With Flares of Inflammatory Bowel Disease,” American Journal of Gastroenterology 113, no. 10 (2018): 1530–1539, 10.1038/s41395-018-0211-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. Spina A., Kerr K. G., Cormican M., et al., “Spectrum of Enteropathogens Detected by the FilmArray GI Panel in a Multicentre Study of Community‐Acquired Gastroenteritis,” Clinical Microbiology and Infections 21, no. 8 (2015): 719–728, 10.1016/j.cmi.2015.04.007. [DOI] [PubMed] [Google Scholar]
  • 30. Hannet I., Engsbro A. L., Pareja J., et al., “Multicenter Evaluation of the New QIAstat Gastrointestinal Panel for the Rapid Syndromic Testing of Acute Gastroenteritis,” European Journal of Clinical Microbiology & Infectious Diseases 38, no. 11 (2019): 2103–2112, 10.1007/s10096-019-03646-4. [DOI] [PubMed] [Google Scholar]
  • 31. Caza M., Tantichalermsin C., Gonzales S., et al., “Evaluation of the QIAstat‐Dx(R) Gastrointestinal Panel 2 for Detection of Viral, Bacterial and Parasitic Pathogens in Fecal Swab Specimens,” Diagnostic Microbiology and Infectious Disease 114 (2026): 117129, 10.1016/j.diagmicrobio.2025.117129. [DOI] [PubMed] [Google Scholar]
  • 32. Newman K. L., Newman G. S., Cannon C. A., and Fang F. C., “Sexually Transmitted Enteric Infections in Men Who Have Sex With Men,” Clinical Microbiology Reviews 38, no. 4 (2025): e0007523, 10.1128/cmr.00075-23. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33. Greninger A. L., Addetia A., Starr K., et al., “International Spread of Multidrug‐Resistant Campylobacter Coli in Men Who Have Sex With Men in Washington State and Quebec, 2015‐2018,” Clinical Infectious Diseases 71, no. 8 (2020): 1896–1904, 10.1093/cid/ciz1060. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34. Newman K. L., Newman G. S., Cybulski R. J., and Fang F. C., “Gastroenteritis in Men Who Have Sex With Men in Seattle, Washington, 2017‐2018,” Clinical Infectious Diseases 71, no. 1 (2020): 109–115, 10.1093/cid/ciz783. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35. Tansarli G. S., Long D. R., Waalkes A., et al., “Genomic Reconstruction and Directed Interventions in a Multidrug‐Resistant Shigellosis Outbreak in Seattle, WA, USA: A Genomic Surveillance Study,” Lancet Infectious Diseases 23, no. 6 (2023): 740–750, 10.1016/s1473-3099(22)00879-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36. Stefanovic A., Alam M. E., Matic N., et al., “Increased Severity of Multidrug‐Resistant Shigella Sonnei Infections in People Experiencing Homelessness,” Clinical Infectious Diseases 80, no. 2 (2025): 339–346, 10.1093/cid/ciae575. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Bateman A. C., Kim Y. J., Guaracao A. I., Mason J. L., Klos R. F., and Warshauer D. M., “Performance and Impact of the Biofire FilmArray Gastrointestinal Panel on a Large Cyclospora Outbreak in Wisconsin, 2018,” Journal of Clinical Microbiology 58, no. 2 (2020): e00028‐25, 10.1128/jcm.01415-19. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38. Toriro R., Pallett S., Woolley S., et al., “Outbreak of Diarrhea Caused by a Novel Cryptosporidium Hominis Subtype During British Military Training in Kenya,” Open Forum Infectious Diseases 11, no. 1 (2024): ofae001, 10.1093/ofid/ofae001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Prakash V. P., LeBlanc L., Alexander‐Scott N. E., et al., “Use of a Culture‐Independent Gastrointestinal Multiplex PCR Panel During a Shigellosis Outbreak: Considerations for Clinical Laboratories and Public Health,” Journal of Clinical Microbiology 53, no. 3 (2015): 1048–1049, 10.1128/jcm.03374-14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Antikainen J., Kantele A., Pakkanen S. H., et al., “A Quantitative Polymerase Chain Reaction Assay for Rapid Detection of 9 Pathogens Directly From Stools of Travelers With Diarrhea,” Clinical Gastroenterology and Hepatology 11, no. 10 (2013): 1300–1307.e3, 10.1016/j.cgh.2013.03.037. [DOI] [PubMed] [Google Scholar]
  • 41. Humphries R. M. and Linscott A. J., “Practical Guidance for Clinical Microbiology Laboratories: Diagnosis of Bacterial Gastroenteritis,” Clinical Microbiology Reviews 28, no. 1 (2015): 3–31, 10.1128/cmr.00073-14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42. Engsbro A. L., Nielsen K. L., Hornum M., and Andersen L. P., “ Laribacter Hongkongensis: Clinical Presentation, Epidemiology and Treatment. A Review of the Literature and Report of the First Case in Denmark,” Infectious Diseases 50, no. 6 (2018): 417–422, 10.1080/23744235.2017.1419373. [DOI] [PubMed] [Google Scholar]
  • 43. Long C., Jones T. F., Vugia D. J., et al., “ Yersinia Pseudotuberculosis and Y. Enterocolitica Infections, FoodNet, 1996‐2007,” Emerging Infectious Diseases 16, no. 3 (2010): 566–567, 10.3201/eid1603.091106. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44. Bradbury R. S., Sapp S. G. H., Potters I., et al., “Where Have all the Diagnostic Morphological Parasitologists Gone?,” Journal of Clinical Microbiology 60, no. 11 (2022): e0098622, 10.1128/jcm.00986-22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45. Garcia L. S., Arrowood M., Kokoskin E., et al., “Practical Guidance for Clinical Microbiology Laboratories: Laboratory Diagnosis of Parasites From the Gastrointestinal Tract,” Clinical Microbiology Reviews 31, no. 1 (2018): e00025‐17, 10.1128/cmr.00025-17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46. Lewinski M. A., Alby K., Babady N. E., et al., “Exploring the Utility of Multiplex Infectious Disease Panel Testing for Diagnosis of Infection in Different Body Sites: A Joint Report of the Association for Molecular Pathology, American Society for Microbiology, Infectious Diseases Society of America, and Pan American Society for Clinical Virology,” Journal of Molecular Diagnostics 25 (2023): 857–875, 10.1016/j.jmoldx.2023.08.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47. Tansarli G. S., Allen D. R., and Fang F. C., “Multiplex Polymerase Chain Reaction Panels for Gastrointestinal Infections: Current Evidence, Regulatory Hurdles, and the Way Forward,” supplement, Open Forum Infectious Diseases 12, no. S2 (2025): S1418–S1430, 10.1093/ofid/ofaf445. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48. Gaudreau C., Rodrigues‐Coutlee S., Pilon P. A., Coutlee F., and Bekal S., “Long‐Lasting Outbreak of Erythromycin‐ and Ciprofloxacin‐Resistant Campylobacter Jejuni Subspecies Jejuni From 2003 to 2013 in Men Who Have Sex With Men, Quebec, Canada,” Clinical Infectious Diseases 61, no. 10 (2015): 1549–1552, 10.1093/cid/civ570. [DOI] [PubMed] [Google Scholar]
  • 49. Sproston E. L., Wimalarathna H. M. L., and Sheppard S. K., “Trends in Fluoroquinolone Resistance in Campylobacter ,” Microbial Genomics 4, no. 8 (2018): e000198, 10.1099/mgen.0.000198. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50. Raccagni A. R., Bruzzesi E., Alberton F., et al., “Sexually Transmitted Enteric Infections in Men Who Have Sex With Men Living With HIV Over 8 Years of Follow‐Up,” Sexually Transmitted Diseases 49, no. 12 (2022): 865, 10.1097/olq.0000000000001704. [DOI] [PubMed] [Google Scholar]
  • 51. Raccagni A. R., Mileto D., Canetti D., et al., “Monkeypox and Pan‐Resistant Campylobacter spp. Infection in Entamoeba Histolytica and Chlamydia Trachomatis Re‐Infection in a Man Who Have Sex With Men,” Journal of Infection 85, no. 4 (2022): 436–480, 10.1016/j.jinf.2022.06.028. [DOI] [PubMed] [Google Scholar]
  • 52. Choi H., Navarathna D. H., Harston B. L., et al., “Case of Extensively Drug‐Resistant Shigella Sonnei Infection, United States,” Emerging Infectious Diseases 29 (2023): 1708–1711, 10.3201/eid2908.230411. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53. Jacqueline C., Carrascoso G. R., Gutierrez‐Fernandez J., et al., “Genetic Characterization of Extensively Drug‐Resistant Shigella Sonnei Infections, Spain, 2021‐2022,” Emerging Infectious Diseases 29, no. 11 (2023): 2370–2373, 10.3201/eid2911.221746. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54. Mason L. C. E., Greig D. R., Cowley L. A., et al., “The Evolution and International Spread of Extensively Drug Resistant Shigella Sonnei ,” Nature Communications 14, no. 1 (2023): 1983, 10.1038/s41467-023-37672-w. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55. Thorley K., Charles H., Greig D. R., et al., “Emergence of Extensively Drug‐Resistant and Multidrug‐Resistant Shigella Flexneri Serotype 2a Associated With Sexual Transmission Among Gay, Bisexual, and Other Men Who Have Sex With Men, in England: A Descriptive Epidemiological Study,” Lancet Infectious Diseases 23, no. 6 (2023): 732–739, 10.1016/s1473-3099(22)00807-6. [DOI] [PubMed] [Google Scholar]
  • 56. Charles H., Sinka K., Simms I., Baker K. S., Godbole G., and Jenkins C., “Trends in Shigellosis Notifications in England, January 2016 to March 2023,” Epidemiology and Infection 152 (2024): e115, 10.1017/s0950268824001006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57. Baumgart S., Phan T., and McKew G., “Epidemiology and Antimicrobial Resistance Rates for Shigella Species in a Resource‐Rich Setting,” Pathology 57, no. 1 (2025): 94–99, 10.1016/j.pathol.2024.07.004. [DOI] [PubMed] [Google Scholar]
  • 58. Caldera J. R., Shaw B., Uslan D. Z., and Yang S., “Cluster of Extensively Drug‐Resistant Shigella Sonnei Carrying bla(CTX‐M‐15) in Los Angeles, California, 2023 to 2024,” American Journal of Infection Control 53, no. 4 (2025): 524–526, 10.1016/j.ajic.2024.12.005. [DOI] [PubMed] [Google Scholar]
  • 59. Liao Y. S., Chen B. H., Hong Y. P., et al., “The Rise in Domestic Shigellosis and the Genomic Characteristics of Shigella Clones Linked to Men Who Have Sex With Men in Taiwan, 2015‒2022,” Microbiology Spectrum 13, no. 4 (2025): e0229024, 10.1128/spectrum.02290-24. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60. Vecilla D. F., Gutierrez M. J. U., Toboso M. C. N., et al., “Genetic Characterization of Extensively Drug‐Resistant bla(CTX‐M‐27) Shigella Sonnei Clusters Among Men Who Have Sex With Men in a Region of Northern Spain,” International Journal of Antimicrobial Agents 65, no. 6 (2025): 107490, 10.1016/j.ijantimicag.2025.107490. [DOI] [PubMed] [Google Scholar]
  • 61. Vecilla D. F., Urrutikoetxea Gutierrez M. J., Nieto Toboso M. C., et al., “First Report of Shigella Sonnei Carrying a bla(CTX‐M‐15) Sexually Transmitted Among Men Who Have Sex With Men,” Infection 53, no. 1 (2025): 443–448, 10.1007/s15010-024-02341-7. [DOI] [PubMed] [Google Scholar]
  • 62. Yoo I. Y., Jo S., Kwon J. A., Han J. H., Lee H. K., and Park Y. J., “Kogene Powerchek Multiplex Real‐Time PCR Kits Versus the BioFire FilmArray Gastrointestinal Panel: Roles of Crossing Point Values and Melting Curves in Interpreting the FilmArray Gastrointestinal Panel,” Annals of Laboratory Medicine 45, no. 6 (2025): 574–582, 10.3343/alm.2025.0047. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63. Bruijnesteijn van Coppenraet L. E., Dullaert‐de Boer M., Ruijs G. J., et al., “Case‐Control Comparison of Bacterial and Protozoan Microorganisms Associated With Gastroenteritis: Application of Molecular Detection,” Clinical Microbiology and Infections 21 (2015): 592.e9‐19, 10.1016/j.cmi.2015.02.007. [DOI] [PubMed] [Google Scholar]
  • 64. Liu J., Platts‐Mills J. A., Juma J., et al., “Use of Quantitative Molecular Diagnostic Methods to Identify Causes of Diarrhoea in Children: A Reanalysis of the GEMS Case‐Control Study,” Lancet 388, no. 10051 (2016): 1291–1301, 10.1016/s0140-6736(16)31529-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65. Crobach M. J. T., Vernon J. J., Loo V. G., et al., “Understanding Clostridium Difficile Colonization,” Clinical Microbiology Reviews 31, no. 2 (2018): e00021‐17, 10.1128/cmr.00021-17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66. Curry S. R., Hecker M. T., O'Hagan J., et al., “Natural History of Clostridioides Difficile Colonization and Infection Following New Acquisition of Carriage in Healthcare Settings: A Prospective Cohort Study,” Clinical Infectious Diseases 77 (2023): 77–83, 10.1093/cid/ciad142. [DOI] [PubMed] [Google Scholar]
  • 67. Burnham C. A. and Carroll K. C., “Diagnosis of Clostridium Difficile Infection: An Ongoing Conundrum for Clinicians and for Clinical Laboratories,” Clinical Microbiology Reviews 26 (2013): 604–630, 10.1128/CMR.00016-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68. Tansarli G. S., Falagas M. E., and Fang F. C., “Clinical Significance of Toxin EIA Positivity in Patients With Suspected Clostridioides Difficile Infection: Systematic Review and meta‐analysis,” Journal of Clinical Microbiology 63, no. 1 (2025): e0097724, 10.1128/jcm.00977-24. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69. van Prehn J., Reigadas E., Vogelzang E. H., et al., “European Society of Clinical Microbiology and Infectious Diseases: 2021 Update on the Treatment Guidance Document for Clostridioides Difficile Infection in Adults,” supplement, Clinical Microbiology and Infections 27, no. S2 (2021): S1–S21, 10.1016/j.cmi.2021.09.038. [DOI] [PubMed] [Google Scholar]
  • 70. McDonald L. C., Gerding D. N., Johnson S., et al., “Clinical Practice Guidelines for Clostridium Difficile Infection in Adults and Children: 2017 Update by the Infectious Diseases Society of America (IDSA) and Society for Healthcare Epidemiology of America (SHEA),” Clinical Infectious Diseases 66, no. 7 (2018): e1–e48, 10.1093/cid/ciy149. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 71. Ford C. D., Lopansri B. K., Hunter B. D., Asch J., and Hoda D., “Multiplexed Gastrointestinal PCR Panels for the Evaluation of Diarrhea in Hematopoietic Stem Cell Transplantation Recipients,” Transplantation and Cellular Therapy 30, no. 8 (2024): 814.e1–814.e7, 10.1016/j.jtct.2024.05.013. [DOI] [PubMed] [Google Scholar]
  • 72. Hebbelstrup J. B., Olsen K. E., Struve C., Krogfelt K. A., and Petersen A. M., “Epidemiology and Clinical Manifestations of Enteroaggregative Escherichia Coli ,” Clinical Microbiology Reviews 27, no. 3 (2014): 614–630, 10.1128/cmr.00112-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 73. Hu J. and Torres A. G., “Enteropathogenic Escherichia Coli: Foe or Innocent Bystander?,” Clinical Microbiology and Infections 21, no. 8 (2015): 729–734, 10.1016/j.cmi.2015.01.015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 74. Mayer H. B. and Wanke C. A., “Enteroaggregative Escherichia coli as a Possible Cause of Diarrhea in an HIV‐Infected Patient,” New England Journal of Medicine 332 (1995): 273–274, 10.1056/nejm199501263320417. [DOI] [PubMed] [Google Scholar]
  • 75. Cornelis G. R., Boland A., Boyd A. P., et al., “The Virulence Plasmid of Yersinia, an Antihost Genome,” Microbiology and Molecular Biology Reviews 62, no. 4 (1998): 1315–1352, 10.1128/mmbr.62.4.1315-1352.1998. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 76. FDA , “510(k) Substantial Equivalence Determination Decision Summary,” accessed February 18, 2026, https://www.accessdata.fda.gov/cdrh_docs/reviews/k140407.pdf#:~:text=histolytica%2C%20the%20only%20Entamoeba%20species%20implicated%20in,may%20cross%2Dreact%20with%20the%20closely%20related%20E.
  • 77. Mergen K., Alleyne L., Fitzhenry R., et al., “Symptomatic Entamoeba dispar Infections Among Men Who Have Sex With Men, New York City, 2018,” Open Forum Infectious Diseases 11, no. 12 (2024): ofae658, 10.1093/ofid/ofae658. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 78. Jesser K. J. and Levy K., “Updates on Defining and Detecting Diarrheagenic Escherichia Coli Pathotypes,” Current Opinion in Infectious Diseases 33, no. 5 (2020): 372–380, 10.1097/qco.0000000000000665. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 79. Frank C., Faber M. S., Askar M., et al., “Large and Ongoing Outbreak of Haemolytic Uraemic Syndrome, Germany, May 2011,” Euro Surveillance 16, no. 21 (2011), 10.2807/ese.16.21.19878-en. [DOI] [PubMed] [Google Scholar]
  • 80. Fasel D., Mellmann A., Cernela N., et al., “Hemolytic Uremic Syndrome in a 65‐Year‐Old Male Linked to a Very Unusual Type of stx2e‐ and Eae‐Harboring O51:H49 Shiga toxin‐producing Escherichia Coli ,” Journal of Clinical Microbiology 52, no. 4 (2014): 1301–1303, 10.1128/jcm.03459-13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 81. de Lira D. R. P., Cavalcanti A. M. F., Pinheiro S. R. S., Orsi H., Dos Santos L. F., and Hernandes R. T., “Identification of a Hybrid Atypical Enteropathogenic and Enteroaggregative Escherichia Coli (aEPEC/EAEC) Clone of Serotype O3:H2 Associated With a Diarrheal Outbreak in Brazil,” Brazilian Journal of Microbiology 52, no. 4 (2021): 2075–2079, 10.1007/s42770-021-00580-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 82. Matic N., Lawson T., Young M., et al., “Melting Curve Analysis Reveals False‐Positive Norovirus Detection in a Molecular Syndromic Panel,” Journal of Clinical Virology 173 (2024): 105697, 10.1016/j.jcv.2024.105697. [DOI] [PubMed] [Google Scholar]
  • 83. bioMérieux , “Field Safety Notice Update. Biofire® FilmArray® Gastrointestinal (GI) Panel—Ref. Number: RFIT‐ASY‐0116 FSCA 5812 – Update to Biofire® Filmarray® Gastrointestinal (GI) Panel Labeling—Norovirus GI/GII Clinical and Analytical Specificity,” accessed February 18, 2026, https://assets.hpra.ie/data/docs/default‐source/product‐updates/fsn/field‐safety‐notices/february‐2025/filmarray‐gastrointestinal‐(gi)‐panel_biofire‐diagnostics‐llc_advice‐regarding‐changesupdates‐made‐to‐instructions‐for‐use.pdf?sfvrsn=a701506e_1.
  • 84. Atmar R. L., Opekun A. R., Gilger M. A., et al., “Norwalk Virus Shedding After Experimental Human Infection,” Emerging Infectious Diseases 14, no. 10 (2008): 1553–1557, 10.3201/eid1410.080117. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 85. Henke‐Gendo C., Harste G., Juergens‐Saathoff B., Mattner F., Deppe H., and Heim A., “New Real‐Time PCR Detects Prolonged Norovirus Excretion in Highly Immunosuppressed Patients and Children,” Journal of Clinical Microbiology 47, no. 9 (2009): 2855–2862, 10.1128/jcm.00448-09. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 86. Aoki Y., Suto A., Mizuta K., Ahiko T., Osaka K., and Matsuzaki Y., “Duration of Norovirus Excretion and the Longitudinal Course of Viral Load in Norovirus‐Infected Elderly Patients,” Journal of Hospital Infection 75, no. 1 (2010): 42–46, 10.1016/j.jhin.2009.12.016. [DOI] [PubMed] [Google Scholar]
  • 87. Bucardo F., “Understanding Asymptomatic Norovirus Infections,” EClinicalMedicine 2–3 (2018): 7–8, 10.1016/j.eclinm.2018.09.005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 88. Sanchez A., Rauch M., Buechner S., Jung‐Hynes B., Beck E., and Bateman A., “Percentage of Culture Confirmation and Melting Curve Analysis Reveals False‐Positive Campylobacter Detection in a Molecular Syndromic Panel,” Journal of Clinical Microbiology 63, no. 8 (2025): e0002825, 10.1128/jcm.00028-25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 89. Freeman C. N., Mehta N., Rabari J., Kosar J., Blondeau J. M., and Hamula C. L., “Retrospective Analysis and Clinical Performance of BD MAX Enteric Pathogen Testing With a Focus on Reliable Identification of Vibrio Species in Stool Samples,” Diagnostic Microbiology and Infectious Disease 111, no. 4 (2025): 116715, 10.1016/j.diagmicrobio.2025.116715. [DOI] [PubMed] [Google Scholar]
  • 90. Gueudet T., Paolini M. C., Buissonniere A., et al., “How to Interpret a Positive Campylobacter PCR Result Using the BD MAX(TM) System in the Absence of Positive Culture?,” Journal of Clinical Medicine 8, no. 12 (2019): 2138, 10.3390/jcm8122138. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 91. Decuir M., Fowler R. C., Cebelinski E., Smith K., Boxrud D., and Medus C., “Evidence of False Positivity for Vibrio Species Tested by Gastrointestinal Multiplex PCR Panels, Minnesota, 2016‐2018,” Open Forum Infectious Diseases 8, no. 6 (2021): ofab247, 10.1093/ofid/ofab247. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.


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