Diagnostics of Fecal Calprotectin Across Gastrointestinal Diagnoses With Presence of Infection

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Fecal calprotectin (FC) is widely used to differentiate inflammatory from non-inflammatory disease, yet real-world performance in the context of infectious comorbidity and indeterminate presentations remains incompletely characterized. Methods A prospective cross-sectional analysis of 702 adults undergoing FC testing within a tertiary-care gastroenterology (GI) network (September–December 2024) was performed to evaluate the influence of recent infection on FC interpretation and diagnostic classification. Classifications included IBD, irritable bowel syndrome (IBS), microscopic colitis, and indeterminate. FC distributions were compared using Kruskal–Wallis testing with Dunn’s correction. Diagnostic performance for identifying IBD was assessed at standard thresholds (≥ 50, 150, 250, and 500 µg/g) with infection stratification. Results Patient stratification by FC resulted in 39.7% confirmed IBD, 16.9% IBS, 41.6% Indeterminate, and 1.7% microscopic colitis. Graded FC values followed: IBS < Microscopic < Indeterminate < IBD; p < 0.001). Median FC was lowest in IBS (19.6 µg/g) and highest in IBD (219 µg/g). Infection was documented in 55% of patients and was associated with modest FC elevation across diagnoses. Diagnostic specificity improved with increasing FC thresholds, rising from 35.7% at ≥ 50 µg/g to 88.7% at ≥ 500 µg/g. Infection reduced specificity at lower thresholds, with greatest interpretive uncertainty from 50–250 µg/g. Conclusion FC remains a valuable biomarker for distinguishing inflammatory from non-inflammatory disease alongside simultaneous infectious consideration. Borderline FC elevations require cautious interpretation in post-infectious settings, with repeat testing after infection resolution. Fecal Calprotectin1 IBD2 IBS3 Infection4 Indeterminate Colitis5 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Inflammatory bowel disease (IBD) as a whole affects 1.6 million people in the United States and health systems consistently bear the burden of associated mortality, long term complications, and lifelong disabilities. The clinical presentation of early IBD flares often overlaps with other inflammatory conditions, including but not limited to IBS, microscopic colitis, and acute gastroenteritis, hence creating diagnostic dilemmas for clinicians [ 1 ]. In healthy tissue, intestinal epithelial cells act as the physical line of defense against pathogens. Dendritic cells, lymphoid cells, neutrophils, and macrophages help maintain this barrier through interaction with pathogenic bacteria [ 1 ]. When pathogenic microorganisms invade the intestinal mucosa, they trigger a neutrophil-predominant inflammatory cascade. Calprotectin, accounting for approximately 60% of cytosolic proteins in neutrophils, is released during this immune activation. Furthermore, calprotectin remains present in fecal content for up to a week after the inciting event due to its high resistance to pancreatic enzymes. This leads to utility in evaluation of IBD as FC levels directly correlate to disease severity [ 2 ]. Moreover, due to cost of and speed of the test in comparison to endoscopy, FC has become a cornerstone in diagnosis of IBD [ 2 ]. However, due to the broad causes of intestinal inflammation, it is difficult to use calprotectin levels to differentiate between some gastrointestinal (GI) disorders [ 3 ]. Nonetheless, in contrast to other inflammatory markers such as ESR and CRP, FC is more sensitive and specific for diagnosis of IBD 4 . Genetics, environment, intestinal barrier, and immune reaction all contribute to pathogenesis of IBD. Specifically, impaired neutrophil recruitment and macrophage activation limit innate immune response, which allow more pathogens to cross the intestinal epithelial barrier. The classification of IBD acts as an overarching term to primarily describe one of two subdivisions: Crohn’s Disease and Ulcerative Colitis (UC) [ 1 ]. Crohn’s disease involves an autoimmune reaction to any portion of the GI tract, most commonly the ileum, which can lead to complications such as strictures, fissures, or neoplasia. Common systemic symptoms include uveitis, erythema nodosum, and oral ulcers. On the other hand, UC solely presents in the abdomen and rectum, typically affecting the rectum first [ 1 ]. As presentations and severities vary, diagnosis of IBD involves a full review of the patient looking at the symptoms, blood markers, and colonoscopy [ 5 ]. Moreover, indeterminate colitis, also known as IBD unclassified, acts as a place holder diagnosis in patients with clinical and histological findings of IBD who cannot yet be given a definitive diagnosis of IBD itself. For example, in cases difficult to differentiate between Crohn’s versus UC, patients receive a temporary diagnosis of indeterminate colitis. Physicians also use this label in patients with symptoms that overlap between IBD and other inflammatory causes [ 6 ]. Irritable bowel syndrome (IBS), one of said other inflammatory causes, also follows a multifactorial pattern, but does not follow the immune processes seen in IBD. Instead it is the result of disruptions in the gut-brain axis, visceral hypersensitivity, GI dysmotility, alterations in gut microbiota, food intolerances, and psychosocial factors that lead to abnormal bowel habits [ 7 ]. Microscopic colitis represents another common cause of chronic or recurrent, nonbloody, watery diarrhea. It consists of two major histological subtypes (collagenous colitis and lymphocytic colitis) which together comprise worldwide incidence of 4.9 cases per 100,000 [ 8 ]. Histologically, microscopic colitis includes either thickened subepithelial collagen band (collagenous colitis) or prominent intraepithelial lymphocytosis (lymphocytic colitis). While its multifactorial nature and unclear definition resemble that of IBD, the pathogenesis of microscopic colitis involves distinct genetic abnormalities and mechanisms of immune destruction that differ from IBD [ 8 ]. Outside of primary GI disorders such as IBD and microscopic colitis, infectious etiology inside and outside the GI tract impact the gut microbiota. For example, SARS-CoV-2 may infect the GI tract and cause inflammation with subsequent damage to the lining of the intestinal mucosa by infection of GI tract cells. This often leads to abdominal pain and diarrhea [ 9 ]. Furthermore, SARS-CoV-2 literature illustrates that SARS-CoV-2 may induce lymphocytic colitis. These patients demonstrated consistently elevated levels of fecal calprotectin and persistent diarrhea, even in the resolution and absence of fecal SARS-CoV-2 RNA [ 8 ]. Urinary tract infections (UTIs) represent a second example of a common infection associated with GI changes. While studies have shown that an unbalanced gut microbiome contributes to the development of UTIs, UTIs have a reciprocal effect causing increased intestinal epithelial permeability 10 . Those more susceptible to UTIs may have underlying GI pathology and those who get UTIs while having GI pathology may be less controlled and therefore have increased fecal calprotectin levels [ 10 ]. This concomitant effect of UTIs and gut health compound fecal calprotectin as a marker and provide an area further studied in this study. Methods Study Design and Population We conducted a prospective, cross-sectional cohort analysis of adult patients who underwent fecal calprotectin (FC) testing between September 2024 and December 2024 within a tertiary-care GI network. All FC assays were ordered as part of routine clinical evaluation for chronic GI symptoms, including diarrhea, abdominal pain, and suspected inflammatory bowel disease (IBD). Patients were classified into four diagnostic categories based on documented clinical diagnoses, endoscopic findings, and histopathology available at the time of FC testing. Categories: Inflammatory Bowel Disease (IBD) : Patients with established Crohn’s disease or ulcerative colitis confirmed by colonoscopy and histologic evidence of chronic mucosal inflammation, consistent with accepted diagnostic criteria. Individuals with a prior confirmed diagnosis of IBD at the time of FC collection were included in this group. Irritable Bowel Syndrome (IBS) : Patients with functional bowel symptoms meeting Rome IV criteria, normal colonoscopic findings (no macroscopic inflammation or ulceration), and no histologic evidence of IBD or microscopic colitis. This group served as the non-inflammatory comparator. Microscopic Colitis : Patients presenting with chronic watery diarrhea and a macroscopically normal colonoscopy. All cases were biopsy-confirmed with histologic confirmation of lymphocytic or collagenous colitis. Indeterminate : Patients who underwent FC testing prior to establishment of a definitive diagnosis and who did not meet criteria for IBD, microscopic colitis, or IBS at the time of sample collection. Many had nonspecific symptoms or were awaiting diagnostic workup. Although follow-up review demonstrated that some patients were subsequently reclassified, FC values were analyzed within this indeterminate category to preserve analytic consistency of clinical context at the time of testing. Causal Framework A directed acyclic graph (DAG) was constructed to represent the hypothesized causal relationships between GI diagnoses, fecal calprotectin levels, and infection status, while accounting for potential unmeasured confounders including age, sex, medication exposure, immune status, antibiotic use, and comorbid conditions. Directed arrows represent assumed causal pathways, and dashed arrows indicate unmeasured confounding variables not directly captured in the dataset (Fig. 1 ). Variables and Definitions FC concentrations were analyzed as a continuous variable and further categorized using clinically recognized thresholds: <50, 50–119, 120–249, 250–499, and ≥ 500 µg/g. Infection status was determined through structured electronic medical record review and defined as the presence of any documented infection within 36 months preceding FC testing. Patients without documented infections at time of FC analysis received non-infectious classification. Secondary analysis further stratified patients with infectious etiology by specific infection. UTIs, upper respiratory infections, pneumonia, central nervous system infections, Clostridioides difficile infections, bacterial gastroenteritis, parasitic infections, and other systemic infections account for the majority of the infectious diseases noted in chart review. The study did not treat infectious categories as mutually exclusive; meaning, individual patients could be classified into multiple infectious categories. Statistical Analysis Descriptive statistics were used to summarize fecal calprotectin distributions across diagnostic groups. Continuous variables were compared using Kruskal–Wallis tests with Dunn’s post-hoc correction for multiple comparisons, and categorical variables were compared using χ² tests or Fisher’s exact tests as appropriate. Diagnostic performance of FC for identifying IBD was evaluated using receiver operating characteristic (ROC) analysis, stratified by diagnostic category. Area under the curve (AUC) values with 95% confidence intervals were calculated. Clinically relevant thresholds (≥ 50, ≥ 150, ≥250, and ≥ 500 µg/g) were assessed using 2×2 contingency tables to estimate sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy. To explore the relationship between fecal calprotectin and infection, multivariable logistic regression models were constructed with infection within 36 months of the outcome. FC was modeled both as a continuous variable and using categorical thresholds, with adjustment for the diagnostic category. Results are reported as odds ratios with 95% confidence intervals. To minimize the visual influence of extreme right-tail values in graphical displays, three fecal calprotectin measurements exceeding 10,000 µg/g were excluded from mean and standard deviation summaries and visualizations. These values were retained for all rank-based analyses, regression models, and diagnostic accuracy assessments. All analyses were performed using Python version 3.12 and R version 4.5.2. Figures were made with R. Results Study Population: A total of 702 patient encounters met inclusion criteria. Of these, 279 (39.7%) had confirmed inflammatory bowel disease (IBD), 292 (41.6%) were classified as indeterminate at the time of fecal calprotectin (FC) testing, 119 (16.9%) had irritable bowel syndrome (IBS), and 12 (1.7%) had biopsy-proven microscopic colitis. This cohort reflects a real-world outpatient population undergoing FC testing for chronic GI complaints. Overall, 55% of patients had a documented infection within 36 months of FC collection, most commonly Clostridioides difficile infection or UTI. Fecal Calprotectin Distributions Across Diagnoses: FC concentrations differed significantly across diagnostic categories (Kruskal–Wallis p < 0.001; Fig. 3 , Table S2). Median FC values were lowest in IBS (19.6 µg/g) and highest in IBD (219 µg/g, IQR 59.6–953), with intermediate values in indeterminate cases (109 µg/g, IQR 59.8–320) and microscopic colitis (148 µg/g). These distributions demonstrated a graded pattern of inflammatory burden (IBS < Microscopic < Indeterminate < IBD), with substantial overlap in the indeterminate group. Indeterminate patients demonstrated a bimodal-to-intermediate distribution with substantial representation in the 50–250 µg/g range, contrasting with IBS (predominantly < 50 µg/g) and IBD (enrichment ≥ 250/≥500 µg/g). Impact of Infection on FC Levels: Across all diagnostic strata, the presence of infection was associated with modestly higher FC values (Fig. 2 , Table S4). Within IBD, infected patients exhibited higher median FC levels than uninfected individuals (248 µg/g vs 198 µg/g). Similar directional increases were observed in indeterminate cases (128 µg/g vs 97 µg/g), microscopic colitis (377 µg/g vs 145 µg/g), and IBS (19.9 µg/g vs 19.0 µg/g) (Table S4). Although the magnitude of increase varied by phenotype, infection-associated elevations were generally smaller than those observed in true inflammatory disease. Analysis by specific infection type demonstrated additional heterogeneity (Table S5). Clostridioides difficile infection was consistently associated with higher median FC levels, particularly in IBD and indeterminate colitis. Viral upper respiratory and UTIs showed FC distributions largely overlapping with those of patients without infection. GI parasitic and central nervous system infections were infrequent but were associated with markedly elevated FC levels in select diseases, accompanied by wide interquartile ranges. Diagnostic Threshold Performance (Unstratified Analysis): Using all available FC values, diagnostic performance for identifying IBD improved with increasing FC thresholds (Table S3). At the conventional ≥ 50 µg/g threshold, sensitivity was high (80.1%) but specificity was limited (35.7%). Increasing the threshold to ≥ 150 µg/g produced a more balanced profile (sensitivity 56.3%, specificity 70.0%). Higher thresholds further increased specificity (77.8% at ≥ 250 µg/g and 88.7% at ≥ 500 µg/g) at the cost of declining sensitivity. Overall diagnostic accuracy increased progressively from 53.3% at ≥ 50 µg/g to 67.4% at ≥ 500 µg/g. Infection-Stratified Diagnostic Performance: Diagnostic performance differed between infected and uninfected patients. Among uninfected individuals, higher thresholds yielded substantial gains in specificity and overall accuracy, with true negatives increasing from 70 at ≥ 50 µg/g to 176 at ≥ 500 µg/g. In contrast, among infected patients, FC remained elevated across diagnoses, resulting in reduced specificity at lower thresholds. Nevertheless, threshold escalation improved discrimination, with true negatives increasing from 81 at ≥ 50 µg/g to 199 at ≥ 500 µg/g. Although sensitivity declined at higher thresholds in both groups, overall accuracy remained acceptable, supporting the clinical utility of threshold modification in the presence of infection. Association Between FC and Infection: In multivariable logistic regression, FC was not independently associated with infection when modeled as a continuous variable (OR 1.00, 95% CI 1.00–1.00; Table 1 ). When evaluated using categorical thresholds, no dose–response relationship was observed. Compared with FC < 50 µg/g, higher FC categories were not associated with increased odds of infection, with the exception of the 50–149 µg/g category, which demonstrated lower odds of infection (OR 0.63, 95% CI 0.41–0.97; Table S6). Adjustment for the diagnostic category did not significantly alter these findings. ROC Analysis: ROC analysis demonstrated poor discrimination of infection risk by FC across most diagnostic groups (Fig. 4 , Table S7). AUC values were near 0.5 for IBD (0.52), IBS (0.49), and indeterminate colitis (0.52), indicating performance no better than chance. Although a higher AUC was observed among patients with microscopic colitis (0.81), confidence intervals were wide and included 0.5, reflecting limited sample size and imprecision. Table 1 Multivariable logistic regression with calprotectin as a continuous variable. Outcome: Infection within 36 months. Reference groups Diagnosis: IBD. Predictor Odds Ratio (95% CI) p value Calprotectin (per µg/g) 1.00 (1.00–1.00) 0.23 Diagnosis: IBS 0.73 (0.47–1.14) 0.17 Diagnosis: Indeterminate 1.08 (0.77–1.51) 0.67 Diagnosis: Microscopic colitis 0.40 (0.11–1.32) 0.15 Table S1 Percent Distribution of Fecal Calprotectin Categories by Diagnosis. Diagnosis < 50 50–119 120–249 250–499 ≥ 500 IBD 22.1% 23.7% 12.9% 14.1% 27.3% IBS 88.0% 12.0% 0.0% 0.0% 0.0% Indeterminate 20.7% 37.5% 20.3% 15.3% 6.1% Microscopic 16.7% 8.3% 41.7% 33.3% 0.0% Table S2 Summary by Diagnostics. Descriptive statistics of fecal calprotectin (µg/g) across diagnostic categories. Diagnosis n mean sd min Q1 median Q3 IBD 249 418 541 5 56 165 556 IBS 108 25.6 20.4 5 9.7 17.6 35.4 Indeterminate 261 157 156 5 54.7 97.1 199 Microscopic 12 203 156 12.9 110 148 352 Table S3 Diagnostic performance of fecal calprotectin thresholds Positive = IBD, Negative = IBS + Indeterminate + Microscopic. Cutoff (µg/g) TP TN FP FN Sensitivity (%) Specificity (%) PPV (%) NPV (%) 50 222 151 272 55 80.1 35.7 44.9 73.3 150 156 296 127 121 56.3 70.0 55.1 71.0 250 131 329 94 146 47.3 77.8 58.2 69.3 500 96 375 48 181 34.7 88.7 66.7 67.4 Table S4 Fecal calprotectin boxplot and P values across infection status and phenotype. Phenotype Infection Median Q1 Q3 P_value Microscopic General infection 377 293 424 0.107 No infection 145 49.5 154 0.107 IBS General infection 18.3 10.9 34.4 0.947 No infection 17.6 9.7 39.5 0.947 IBD General infection 199 55.6 794 0.968 No infection 191 61.2 759 0.968 Indeterminate General infection 116 54 278 0.694 No infection 95.6 61 228 0.694 Table S5 Fecal calprotectin boxplot values across infection type and phenotype. Phenotype Infection N Median IQR Microscopic C diff 12 148 110.425–351.5 General infection 4 377 293–424.25 No infection 8 145 49.5–154.5 Other 3 348 238–377 URI (Viral) 2 252 138.425–365.475 UTI 1 348 348–348 IBS C diff 109 17.7 9.7–37.1 GI Parasite 4 30.2 16.55–45.375 General infection 52 18.3 10.9–34.45 No infection 57 17.6 9.7–39.5 Other 18 18.6 11.85–32.8 URI (Viral) 24 18.3 12.075–31.7 UTI 25 19.6 11.7–34.3 IBD C diff 264 196 58.25–788 CNS 2 746 514–978 GI Parasite 2 59 43–75 General infection 147 199 55.6–794.5 No infection 117 191 61.2–759 Other 37 195 69.3–585 URI (Viral) 74 218 67.425–727.75 UTI 44 186 40.65–543 Indeterminate C diff 271 102 58–248 CNS 2 75.6 69.1–82.1 GI Parasite 5 350 128–449 General infection 157 116 54–278 No infection 114 95.6 61–227.5 Other 37 137 60.1–324 URI (Viral) 77 129 55.8–280 UTI 76 101 54.225–171.25 Table S6 Multivariable logistic regression with calprotectin categories. Outcome: Infection within 36 months. Reference groups: Calprotectin < 50 µg/g, Diagnosis: IBD Predictor Odds Ratio (95% CI) p value Calprotectin 50–149 0.63 (0.41–0.97) 0.037 Calprotectin 150–249 0.96 (0.52–1.79) 0.89 Calprotectin 250–499 0.91 (0.52–1.61) 0.75 Calprotectin ≥ 500 0.95 (0.58–1.54) 0.82 Diagnosis: IBS 0.62 (0.38–1.02) 0.061 Diagnosis: Indeterminate 1.12 (0.80–1.59) 0.51 Diagnosis: Microscopic colitis 0.41 (0.11–1.36) 0.16 Table S7 ROC analysis of fecal calprotectin for infection prediction by diagnosis Diagnosis AUC (95% CI) IBD 0.52 (0.45–0.59) IBS 0.49 (0.39–0.60) Indeterminate 0.52 (0.45–0.59) Microscopic colitis 0.81 (0.50–1.00) Discussion Fecal calprotectin (FC) levels differed substantially across diagnostic categories. Patients with IBD (n = 249) had the highest mean fecal calprotectin concentration (418 µg/g, SD 541), followed by microscopic colitis (n = 12; mean 203 µg/g, SD 156) and indeterminate (n = 261; mean 157 µg/g, SD 156). In contrast, patients with IBS (n = 108) demonstrated markedly lower values, with a mean FC of 25.6 µg/g (SD 20.4). These distributions illustrate a clear inflammatory gradient, with progressively higher FC concentrations observed from IBS to indeterminate disease, microscopic colitis, and topped with IBD. These values generally align with the trends found in literature. In a study with 30 patients with IBS, they reported a mean FC level of 38.2 ± 14.6 µg/g [ 12 ]. Both our findings and those of the literature can be mechanistically explained as the lack of autoimmune intestinal inflammation seen in IBS as opposed to IBD. In regard to indeterminate colitis, literature currently lacks consensus on typical FC values. The third level of the gradient, microscopic colitis, was reported by a meta analysis to have a mean FC level of 214.3 ± 176.7 µg/g [ 13 ]. Even with a smaller n value, in comparison of our microscopic colitis cohort to that of literature, they share a similar numerical basis. Lastly, in a study of 93 patients with active IBD the mean FC level was 906.3 ± 1,484.9 µg/g in UC and 1,054.1 ± 1,252.5 µg/g in Crohn’s. In those with mucosal healing, that study reported mean FC levels of 85.5 ± 55.6 µg/g [ 14 ]. Our study reported an average FC of 418 µg/g ± 541µg/g in the 249 patients with IBD, with no discrimination between active and controlled disease. Furthermore, previous research has shown that patients with C. diff infection have significantly higher levels of fecal calprotectin (FC) compared to the FC levels of healthy patients. When C. diff was compounded with a concomitant UC diagnosis the FC was higher than that of UC patients without C. diff. That said, no diagnostic threshold was established 15 . That study also examined the impact of mild vs severe C. diff infection and yielded a sensitivity and specificity of 57% and 88% for non-severe C. diff infection and mild C. diff infection respectively [ 15 ]. On the contrary, our study did not find significant increases in FC following C. diff when combined with concomitant diagnoses such as UC. Moreover, SARS-CoV-2 infection has shown elevated levels of FC 8 as well as increased the number of gut brain interaction disorders from pre-pandemic to post pandemic [ 8 , 16 ]. The aforementioned studies indicated elevated FC levels but lacked specification of differences in FC during infection and post infection. Our data suggests that infection blurs the line of our moderate range fecal calprotectin levels especially in IBD and Indeterminate where the 250 µg/g range had similar values between infection and non-infection (Table S5), but overall upper respiratory infections do not significantly impact already diagnosed conditions.Thereforecaution should be used in the presence of infection during clinical evaluation of GI symptoms. Figure 6 consequently suggests a framework for proceeding after FC levels have been pulled and there is suspicion for a concomitant infection. Additionally, in a study of 84 patients, concentrations of FC in patients with positive bacterial stool cultures were significantly elevated compared with those with positive viral stool studies [ 17 ]. When we stratified by specific infection subtype, FC values for common infections, including viral upper respiratory and urinary tract infections, demonstrated substantial overlap with those of patients without infection, with no statistically significant differences observed (Table S4). The lack of statistical significance in this portion of our study may be attributed to the larger allotted time for infection and allowance of multiple infection subtypes per FC level. Lastly, our findings highlight that while FC remains a highly useful marker for identifying inflammatory bowel disease, concurrent infections confounds diagnostic accuracy. In clinical practice, borderline FC elevations (100–300 µg/g) in recently infected patients should be interpreted cautiously and often warrant retesting after resolution of infection. Across this large, heterogeneous outpatient cohort, FC reliably differentiated IBD from non-IBD conditions, with predictable improvements in specificity as diagnostic thresholds increased. Infection modestly elevated FC across all diagnoses, but the magnitude of increase was substantially smaller than that observed in true intestinal inflammation. These findings emphasize: FC retains diagnostic value in the presence of infection, though thresholds may require careful contextual interpretation, and indeterminate and borderline FC values (50–250 µg/g) represent the greatest interpretive challenge, particularly when concurrent infection is present. Based on these findings, we propose a pragmatic clinical framework in which infection status primarily modifies interpretation of borderline fecal calprotectin values, while higher thresholds retain diagnostic specificity for IBD (Fig. 5 ). In this large, real-world outpatient cohort, FC demonstrated a clear and progressive gradient across gastrointestinal phenotypes, with the lowest values observed in IBS and the highest in IBD. Fecal calprotectin remained a useful tool for distinguishing inflammatory from non-inflammatory disease; however, its diagnostic performance was meaningfully influenced by concurrent or recent infection. Infection was associated with modest elevation of FC across all diagnostic groups, reducing specificity at lower thresholds and contributing to diagnostic uncertainty, particularly within the borderline range of 50–250 µg/g. Higher FC thresholds were associated with improved specificity and overall diagnostic accuracy, even among infected patients, supporting threshold escalation as a pragmatic strategy in complex clinical settings. These findings underscore the importance of contextual interpretation of FC results. In patients with recent infection, borderline elevations should be interpreted cautiously and may warrant repeat testing after infection resolution rather than immediate escalation to invasive evaluation. Overall, FC remains a valuable biomarker when integrated with clinical context, infection history, and diagnostic uncertainty. Future prospective studies should examine the impact of infection timing, antibiotic exposure, and incorporation of complementary clinical and laboratory markers to further refine diagnostic pathways and reduce indeterminate classifications. This study has several important limitations. First, although the cohort was prospectively assembled, infection status was determined through electronic medical record documentation, which may be subject to incomplete capture or variable timing relative to FC collection. The 36-month infection window likely includes both remote and recent infections, limiting the ability to precisely attribute FC elevations to active or resolving infectious processes at the time of testing. Second, the indeterminate diagnostic category reflects real-world clinical uncertainty but is inherently heterogeneous; some patients were later reclassified, which may have introduced misclassification bias despite our decision to analyze FC values based on diagnosis at the time of testing. Third, FC assays were obtained as part of routine clinical care, and potential variability related to sample handling, timing relative to symptom onset, or assay-specific factors could not be fully controlled. Extreme FC values demonstrated wide dispersion, reflecting real-world biological variability but also contributing to overlap between diagnostic groups. Finally, this analysis focused on FC as a standalone biomarker. Other clinically relevant variables such as symptom duration, inflammatory blood markers, antibiotic exposure, and treatment status were not incorporated into multivariable models. As a result, the findings should be interpreted as reflective of FC performance in isolation rather than as part of a comprehensive diagnostic algorithm. Declarations Conflicts of Interest The authors declare no conflict of interest. Ethics The study was approved by the Institutional Review Board University of Illinois College of Medicine at Peoria 2356668-3. All authors comply with the journal's ethical policies. Funding The author has nothing to report. Author Contribution Conceptualization, EB, DH, MS, AD, JF.; Methodology, EB, JF, MS, AD.; Validation, EB, JF, MS, AD, BO, DH.; Investigation, EB, BO, MS, DH, AD.; resources, JF.; data curation, EB.; writing—original draft preparation, EB, and LW..; writing—review and editing, EB, and LW; supervision, EB., JF.; project administration, EB,. JF. 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The usefulness of fecal calprotectin in assessing inflammatory bowel disease activity. Korean J Intern Med. 2019;34(1):72–80. https://doi.org/10.3904/kjim.2016.324 . Wen BJ, Te LG, Liu XX, Zhao JH. The value of fecal calprotectin in Clostridioides difficile infection: A systematic review. Front Physiol. 2022;13:881816. https://doi.org/10.3389/fphys.2022.881816 . Palsson O, Simren M, Sperber AD, Bangdiwala S, Hreinsson JP, Aziz I. (n.d.). The Prevalence and Burden of Disorders of Gut-Brain Interaction (DGBI) Before vs After the COVID-19. Duman M, Gencpinar P, Biçmen M, Arslan N, Özden Ö, Üzüm Ö, Çelik D, Sayıner AA, Gülay Z. Fecal calprotectin: can be used to distinguish between bacterial and viral gastroenteritis in children? Am J Emerg Med. 2015;33(10):1436–9. https://doi.org/10.1016/j.ajem.2015.07.007 . Supplemental. Additional Declarations No competing interests reported. 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Baumgartner","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtElEQVRIiWNgGAWjYJACCYaKf3IMzCAmG9FazhwwJlELY9uBxAYGYrXws589eLuC7U76huPMDxg+lB0mrEWyJy/Z8gzPs9wNh9kMGGecI0KLwYEcM8kGCWagFh4GZt42IrTYn38D1GLAnG4A0vKXGC0GEiBbEg4ngLUwEqNF4sYbY8uGA2mGM4F+OdhzLp2wFv7+HMObjf9s5PnOH3744EeZNWEtKOAAiepHwSgYBaNgFOACADhtOb8bYHsUAAAAAElFTkSuQmCC","orcid":"","institution":"University of Illinois at Chicago","correspondingAuthor":true,"prefix":"","firstName":"Elodie","middleName":"","lastName":"Baumgartner","suffix":""},{"id":574492737,"identity":"fa37eaac-2962-4e1d-b1d2-781595da45e6","order_by":1,"name":"Lexi Weltin","email":"","orcid":"","institution":"University of Illinois at Chicago","correspondingAuthor":false,"prefix":"","firstName":"Lexi","middleName":"","lastName":"Weltin","suffix":""},{"id":574492738,"identity":"25864fa6-e495-481b-b61d-c9a699e537a9","order_by":2,"name":"Max Spiro","email":"","orcid":"","institution":"University of Illinois at Chicago","correspondingAuthor":false,"prefix":"","firstName":"Max","middleName":"","lastName":"Spiro","suffix":""},{"id":574492740,"identity":"c05d15bb-17da-43df-b501-51f2f0b3c423","order_by":3,"name":"Daniel Henley","email":"","orcid":"","institution":"University of Illinois at Chicago","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Henley","suffix":""},{"id":574492748,"identity":"138afe29-ac0a-4442-aa02-8f906852c50d","order_by":4,"name":"Bret Olson","email":"","orcid":"","institution":"University of Illinois at Chicago","correspondingAuthor":false,"prefix":"","firstName":"Bret","middleName":"","lastName":"Olson","suffix":""},{"id":574492753,"identity":"57f66553-788c-45fd-b336-6d738a7c857c","order_by":5,"name":"Aneal Dayal","email":"","orcid":"","institution":"University of Illinois at Chicago","correspondingAuthor":false,"prefix":"","firstName":"Aneal","middleName":"","lastName":"Dayal","suffix":""},{"id":574492760,"identity":"53e9a872-06fe-414d-b6e2-ca1088215f2a","order_by":6,"name":"John Farrell","email":"","orcid":"","institution":"University of Illinois at Chicago","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"","lastName":"Farrell","suffix":""}],"badges":[],"createdAt":"2026-01-12 01:08:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8576222/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8576222/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":100546553,"identity":"de2dba73-4c7e-43eb-be02-d6bb475a56e7","added_by":"auto","created_at":"2026-01-19 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15:05:32","extension":"png","order_by":16,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":36563,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8576222/v1/5ac69a736c9e4905913fface.png"},{"id":100432445,"identity":"8dbb6504-1aca-4aca-9a39-3576e4f08da0","added_by":"auto","created_at":"2026-01-16 15:05:32","extension":"xml","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":102368,"visible":true,"origin":"","legend":"","description":"","filename":"dd9daf9bb510454fad421a88d0c916861structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8576222/v1/c6cbf020342ed1c58a12f20f.xml"},{"id":100547127,"identity":"e8f2926d-50b3-4ea7-8a48-bb3da1e922a9","added_by":"auto","created_at":"2026-01-19 08:14:35","extension":"html","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":113507,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8576222/v1/772cd771030c6915ad7049c0.html"},{"id":100546334,"identity":"87b12a9f-abaa-49df-9499-f3100bf8ae6a","added_by":"auto","created_at":"2026-01-19 08:06:10","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":157711,"visible":true,"origin":"","legend":"\u003cp\u003eDAG Illustrating Exposure, Outcome, and Unmeasured Confounders Affecting Fecal Calprotectin Across GI Diagnoses. Illustrates the complexity and interconnectedness associated with diagnosis. Produced with Daggity [11].\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8576222/v1/8c4cd456319addf3dafacc15.png"},{"id":100432429,"identity":"becbe229-3835-4038-92c0-54432607477b","added_by":"auto","created_at":"2026-01-16 15:05:32","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":373277,"visible":true,"origin":"","legend":"\u003cp\u003eBoxplots of FC (µg/g) Distributions. Demonstrates variability across diagnostic groups (IBS, Microscopic Colitis, Indeterminate, IBD) by presence and type of infection.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8576222/v1/8499397a50632c24693466b1.jpeg"},{"id":100432444,"identity":"483f3c07-199b-42e6-aa8c-ba2f14178a9b","added_by":"auto","created_at":"2026-01-16 15:05:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":66317,"visible":true,"origin":"","legend":"\u003cp\u003eFecal Calprotectin by Diagnosis. Box plot showing fecal calprotectin (µg/g) distributions across diagnostic groups (IBS, Microscopic Colitis, Indeterminate, IBD).\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8576222/v1/1cd9c9cc94ecb2b405acaa33.png"},{"id":100432431,"identity":"1c904996-a699-4b20-aaa6-9fdd26d524d8","added_by":"auto","created_at":"2026-01-16 15:05:32","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":112100,"visible":true,"origin":"","legend":"\u003cp\u003eROC Curves Stratified by Infection Status. Comparison of ROC performance between infected and uninfected subgroups.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8576222/v1/8d3dc5694feab274ec28fbbe.png"},{"id":100432434,"identity":"fb6b7b1c-167f-4c91-9a6d-ae6c3e4a9396","added_by":"auto","created_at":"2026-01-16 15:05:32","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":219550,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of Interpretation and Recommendations.\u003cstrong\u003e \u003c/strong\u003eRecommendations per FC value based upon observed test characteristics.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8576222/v1/ab8725ff2f812f6661602acc.png"},{"id":100432435,"identity":"3300da8f-2c87-432a-b54b-88675f1fc15f","added_by":"auto","created_at":"2026-01-16 15:05:32","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":112701,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of Patients in Each Diagnostic Category Stratified by FC range.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8576222/v1/b751402c5f4e98d232eaf2c3.png"},{"id":102964014,"identity":"b27de7da-22d1-4eea-98e0-06d90b3fd382","added_by":"auto","created_at":"2026-02-19 04:21:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1811929,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8576222/v1/f0f10956-188a-4dd3-8e91-dd791fde75f2.pdf"},{"id":100432427,"identity":"19086bd1-7d69-4db7-ba2f-6d8dd69f142e","added_by":"auto","created_at":"2026-01-16 15:05:32","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":155352,"visible":true,"origin":"","legend":"","description":"","filename":"Supplemental.docx","url":"https://assets-eu.researchsquare.com/files/rs-8576222/v1/69dddae6b936dbfccdd41448.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Diagnostics of Fecal Calprotectin Across Gastrointestinal Diagnoses With Presence of Infection","fulltext":[{"header":"Introduction","content":"\u003cp\u003eInflammatory bowel disease (IBD) as a whole affects 1.6\u0026nbsp;million people in the United States and health systems consistently bear the burden of associated mortality, long term complications, and lifelong disabilities. The clinical presentation of early IBD flares often overlaps with other inflammatory conditions, including but not limited to IBS, microscopic colitis, and acute gastroenteritis, hence creating diagnostic dilemmas for clinicians [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn healthy tissue, intestinal epithelial cells act as the physical line of defense against pathogens. Dendritic cells, lymphoid cells, neutrophils, and macrophages help maintain this barrier through interaction with pathogenic bacteria [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. When pathogenic microorganisms invade the intestinal mucosa, they trigger a neutrophil-predominant inflammatory cascade. Calprotectin, accounting for approximately 60% of cytosolic proteins in neutrophils, is released during this immune activation. Furthermore, calprotectin remains present in fecal content for up to a week after the inciting event due to its high resistance to pancreatic enzymes. This leads to utility in evaluation of IBD as FC levels directly correlate to disease severity [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Moreover, due to cost of and speed of the test in comparison to endoscopy, FC has become a cornerstone in diagnosis of IBD [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, due to the broad causes of intestinal inflammation, it is difficult to use calprotectin levels to differentiate between some gastrointestinal (GI) disorders [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Nonetheless, in contrast to other inflammatory markers such as ESR and CRP, FC is more sensitive and specific for diagnosis of IBD\u003csup\u003e4\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGenetics, environment, intestinal barrier, and immune reaction all contribute to pathogenesis of IBD. Specifically, impaired neutrophil recruitment and macrophage activation limit innate immune response, which allow more pathogens to cross the intestinal epithelial barrier. The classification of IBD acts as an overarching term to primarily describe one of two subdivisions: Crohn\u0026rsquo;s Disease and Ulcerative Colitis (UC) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Crohn\u0026rsquo;s disease involves an autoimmune reaction to any portion of the GI tract, most commonly the ileum, which can lead to complications such as strictures, fissures, or neoplasia. Common systemic symptoms include uveitis, erythema nodosum, and oral ulcers. On the other hand, UC solely presents in the abdomen and rectum, typically affecting the rectum first [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. As presentations and severities vary, diagnosis of IBD involves a full review of the patient looking at the symptoms, blood markers, and colonoscopy [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMoreover, indeterminate colitis, also known as IBD unclassified, acts as a place holder diagnosis in patients with clinical and histological findings of IBD who cannot yet be given a definitive diagnosis of IBD itself. For example, in cases difficult to differentiate between Crohn\u0026rsquo;s versus UC, patients receive a temporary diagnosis of indeterminate colitis. Physicians also use this label in patients with symptoms that overlap between IBD and other inflammatory causes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Irritable bowel syndrome (IBS), one of said other inflammatory causes, also follows a multifactorial pattern, but does not follow the immune processes seen in IBD. Instead it is the result of disruptions in the gut-brain axis, visceral hypersensitivity, GI dysmotility, alterations in gut microbiota, food intolerances, and psychosocial factors that lead to abnormal bowel habits [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMicroscopic colitis represents another common cause of chronic or recurrent, nonbloody, watery diarrhea. It consists of two major histological subtypes (collagenous colitis and lymphocytic colitis) which together comprise worldwide incidence of 4.9 cases per 100,000 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Histologically, microscopic colitis includes either thickened subepithelial collagen band (collagenous colitis) or prominent intraepithelial lymphocytosis (lymphocytic colitis). While its multifactorial nature and unclear definition resemble that of IBD, the pathogenesis of microscopic colitis involves distinct genetic abnormalities and mechanisms of immune destruction that differ from IBD [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOutside of primary GI disorders such as IBD and microscopic colitis, infectious etiology inside and outside the GI tract impact the gut microbiota. For example, SARS-CoV-2 may infect the GI tract and cause inflammation with subsequent damage to the lining of the intestinal mucosa by infection of GI tract cells. This often leads to abdominal pain and diarrhea [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Furthermore, SARS-CoV-2 literature illustrates that SARS-CoV-2 may induce lymphocytic colitis. These patients demonstrated consistently elevated levels of fecal calprotectin and persistent diarrhea, even in the resolution and absence of fecal SARS-CoV-2 RNA [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUrinary tract infections (UTIs) represent a second example of a common infection associated with GI changes. While studies have shown that an unbalanced gut microbiome contributes to the development of UTIs, UTIs have a reciprocal effect causing increased intestinal epithelial permeability\u003csup\u003e10\u003c/sup\u003e. Those more susceptible to UTIs may have underlying GI pathology and those who get UTIs while having GI pathology may be less controlled and therefore have increased fecal calprotectin levels [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This concomitant effect of UTIs and gut health compound fecal calprotectin as a marker and provide an area further studied in this study.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy Design and Population\u003c/p\u003e \u003cp\u003eWe conducted a prospective, cross-sectional cohort analysis of adult patients who underwent fecal calprotectin (FC) testing between September 2024 and December 2024 within a tertiary-care GI network. All FC assays were ordered as part of routine clinical evaluation for chronic GI symptoms, including diarrhea, abdominal pain, and suspected inflammatory bowel disease (IBD). Patients were classified into four diagnostic categories based on documented clinical diagnoses, endoscopic findings, and histopathology available at the time of FC testing.\u003c/p\u003e \u003cp\u003eCategories:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eInflammatory Bowel Disease (IBD)\u003c/span\u003e: Patients with established Crohn\u0026rsquo;s disease or ulcerative colitis confirmed by colonoscopy and histologic evidence of chronic mucosal inflammation, consistent with accepted diagnostic criteria. Individuals with a prior confirmed diagnosis of IBD at the time of FC collection were included in this group.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eIrritable Bowel Syndrome (IBS)\u003c/span\u003e: Patients with functional bowel symptoms meeting Rome IV criteria, normal colonoscopic findings (no macroscopic inflammation or ulceration), and no histologic evidence of IBD or microscopic colitis. This group served as the non-inflammatory comparator.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eMicroscopic Colitis\u003c/span\u003e: Patients presenting with chronic watery diarrhea and a macroscopically normal colonoscopy. All cases were biopsy-confirmed with histologic confirmation of lymphocytic or collagenous colitis.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eIndeterminate\u003c/span\u003e: Patients who underwent FC testing prior to establishment of a definitive diagnosis and who did not meet criteria for IBD, microscopic colitis, or IBS at the time of sample collection. Many had nonspecific symptoms or were awaiting diagnostic workup. Although follow-up review demonstrated that some patients were subsequently reclassified, FC values were analyzed within this indeterminate category to preserve analytic consistency of clinical context at the time of testing.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCausal Framework\u003c/h2\u003e \u003cp\u003eA directed acyclic graph (DAG) was constructed to represent the hypothesized causal relationships between GI diagnoses, fecal calprotectin levels, and infection status, while accounting for potential unmeasured confounders including age, sex, medication exposure, immune status, antibiotic use, and comorbid conditions. Directed arrows represent assumed causal pathways, and dashed arrows indicate unmeasured confounding variables not directly captured in the dataset (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eVariables and Definitions\u003c/h3\u003e\n\u003cp\u003eFC concentrations were analyzed as a continuous variable and further categorized using clinically recognized thresholds: \u0026lt;50, 50\u0026ndash;119, 120\u0026ndash;249, 250\u0026ndash;499, and \u0026ge;\u0026thinsp;500 \u0026micro;g/g. Infection status was determined through structured electronic medical record review and defined as the presence of any documented infection within 36 months preceding FC testing. Patients without documented infections at time of FC analysis received non-infectious classification.\u003c/p\u003e \u003cp\u003eSecondary analysis further stratified patients with infectious etiology by specific infection. UTIs, upper respiratory infections, pneumonia, central nervous system infections, Clostridioides difficile infections, bacterial gastroenteritis, parasitic infections, and other systemic infections account for the majority of the infectious diseases noted in chart review. The study did not treat infectious categories as mutually exclusive; meaning, individual patients could be classified into multiple infectious categories.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eDescriptive statistics were used to summarize fecal calprotectin distributions across diagnostic groups. Continuous variables were compared using Kruskal\u0026ndash;Wallis tests with Dunn\u0026rsquo;s post-hoc correction for multiple comparisons, and categorical variables were compared using χ\u0026sup2; tests or Fisher\u0026rsquo;s exact tests as appropriate. Diagnostic performance of FC for identifying IBD was evaluated using receiver operating characteristic (ROC) analysis, stratified by diagnostic category. Area under the curve (AUC) values with 95% confidence intervals were calculated. Clinically relevant thresholds (\u0026ge;\u0026thinsp;50, \u0026ge;\u0026thinsp;150, \u0026ge;250, and \u0026ge;\u0026thinsp;500 \u0026micro;g/g) were assessed using 2\u0026times;2 contingency tables to estimate sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy. To explore the relationship between fecal calprotectin and infection, multivariable logistic regression models were constructed with infection within 36 months of the outcome.\u003c/p\u003e \u003cp\u003eFC was modeled both as a continuous variable and using categorical thresholds, with adjustment for the diagnostic category. Results are reported as odds ratios with 95% confidence intervals. To minimize the visual influence of extreme right-tail values in graphical displays, three fecal calprotectin measurements exceeding 10,000 \u0026micro;g/g were excluded from mean and standard deviation summaries and visualizations. These values were retained for all rank-based analyses, regression models, and diagnostic accuracy assessments. All analyses were performed using Python version 3.12 and R version 4.5.2. Figures were made with R.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStudy Population:\u003c/h2\u003e \u003cp\u003eA total of 702 patient encounters met inclusion criteria. Of these, 279 (39.7%) had confirmed inflammatory bowel disease (IBD), 292 (41.6%) were classified as indeterminate at the time of fecal calprotectin (FC) testing, 119 (16.9%) had irritable bowel syndrome (IBS), and 12 (1.7%) had biopsy-proven microscopic colitis. This cohort reflects a real-world outpatient population undergoing FC testing for chronic GI complaints. Overall, 55% of patients had a documented infection within 36 months of FC collection, most commonly Clostridioides difficile infection or UTI.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eFecal Calprotectin Distributions Across Diagnoses:\u003c/h2\u003e \u003cp\u003eFC concentrations differed significantly across diagnostic categories (Kruskal\u0026ndash;Wallis p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Table S2). Median FC values were lowest in IBS (19.6 \u0026micro;g/g) and highest in IBD (219 \u0026micro;g/g, IQR 59.6\u0026ndash;953), with intermediate values in indeterminate cases (109 \u0026micro;g/g, IQR 59.8\u0026ndash;320) and microscopic colitis (148 \u0026micro;g/g). These distributions demonstrated a graded pattern of inflammatory burden (IBS\u0026thinsp;\u0026lt;\u0026thinsp;Microscopic\u0026thinsp;\u0026lt;\u0026thinsp;Indeterminate\u0026thinsp;\u0026lt;\u0026thinsp;IBD), with substantial overlap in the indeterminate group. Indeterminate patients demonstrated a bimodal-to-intermediate distribution with substantial representation in the 50\u0026ndash;250 \u0026micro;g/g range, contrasting with IBS (predominantly\u0026thinsp;\u0026lt;\u0026thinsp;50 \u0026micro;g/g) and IBD (enrichment\u0026thinsp;\u0026ge;\u0026thinsp;250/\u0026ge;500 \u0026micro;g/g).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eImpact of Infection on FC Levels:\u003c/h3\u003e\n\u003cp\u003eAcross all diagnostic strata, the presence of infection was associated with modestly higher FC values (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table S4). Within IBD, infected patients exhibited higher median FC levels than uninfected individuals (248 \u0026micro;g/g vs 198 \u0026micro;g/g). Similar directional increases were observed in indeterminate cases (128 \u0026micro;g/g vs 97 \u0026micro;g/g), microscopic colitis (377 \u0026micro;g/g vs 145 \u0026micro;g/g), and IBS (19.9 \u0026micro;g/g vs 19.0 \u0026micro;g/g) (Table S4). Although the magnitude of increase varied by phenotype, infection-associated elevations were generally smaller than those observed in true inflammatory disease. Analysis by specific infection type demonstrated additional heterogeneity (Table S5). Clostridioides difficile infection was consistently associated with higher median FC levels, particularly in IBD and indeterminate colitis. Viral upper respiratory and UTIs showed FC distributions largely overlapping with those of patients without infection. GI parasitic and central nervous system infections were infrequent but were associated with markedly elevated FC levels in select diseases, accompanied by wide interquartile ranges.\u003c/p\u003e\n\u003ch3\u003eDiagnostic Threshold Performance (Unstratified Analysis):\u003c/h3\u003e\n\u003cp\u003eUsing all available FC values, diagnostic performance for identifying IBD improved with increasing FC thresholds (Table S3). At the conventional\u0026thinsp;\u0026ge;\u0026thinsp;50 \u0026micro;g/g threshold, sensitivity was high (80.1%) but specificity was limited (35.7%). Increasing the threshold to \u0026ge;\u0026thinsp;150 \u0026micro;g/g produced a more balanced profile (sensitivity 56.3%, specificity 70.0%). Higher thresholds further increased specificity (77.8% at \u0026ge;\u0026thinsp;250 \u0026micro;g/g and 88.7% at \u0026ge;\u0026thinsp;500 \u0026micro;g/g) at the cost of declining sensitivity. Overall diagnostic accuracy increased progressively from 53.3% at \u0026ge;\u0026thinsp;50 \u0026micro;g/g to 67.4% at \u0026ge;\u0026thinsp;500 \u0026micro;g/g.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eInfection-Stratified Diagnostic Performance:\u003c/h2\u003e \u003cp\u003eDiagnostic performance differed between infected and uninfected patients. Among uninfected individuals, higher thresholds yielded substantial gains in specificity and overall accuracy, with true negatives increasing from 70 at \u0026ge;\u0026thinsp;50 \u0026micro;g/g to 176 at \u0026ge;\u0026thinsp;500 \u0026micro;g/g. In contrast, among infected patients, FC remained elevated across diagnoses, resulting in reduced specificity at lower thresholds. Nevertheless, threshold escalation improved discrimination, with true negatives increasing from 81 at \u0026ge;\u0026thinsp;50 \u0026micro;g/g to 199 at \u0026ge;\u0026thinsp;500 \u0026micro;g/g. Although sensitivity declined at higher thresholds in both groups, overall accuracy remained acceptable, supporting the clinical utility of threshold modification in the presence of infection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAssociation Between FC and Infection:\u003c/h2\u003e \u003cp\u003eIn multivariable logistic regression, FC was not independently associated with infection when modeled as a continuous variable (OR 1.00, 95% CI 1.00\u0026ndash;1.00; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). When evaluated using categorical thresholds, no dose\u0026ndash;response relationship was observed. Compared with FC\u0026thinsp;\u0026lt;\u0026thinsp;50 \u0026micro;g/g, higher FC categories were not associated with increased odds of infection, with the exception of the 50\u0026ndash;149 \u0026micro;g/g category, which demonstrated lower odds of infection (OR 0.63, 95% CI 0.41\u0026ndash;0.97; Table S6). Adjustment for the diagnostic category did not significantly alter these findings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eROC Analysis:\u003c/h2\u003e \u003cp\u003eROC analysis demonstrated poor discrimination of infection risk by FC across most diagnostic groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Table S7). AUC values were near 0.5 for IBD (0.52), IBS (0.49), and indeterminate colitis (0.52), indicating performance no better than chance. Although a higher AUC was observed among patients with microscopic colitis (0.81), confidence intervals were wide and included 0.5, reflecting limited sample size and imprecision.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable logistic regression with calprotectin as a continuous variable. Outcome: Infection within 36 months. Reference groups Diagnosis: IBD.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds Ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalprotectin (per \u0026micro;g/g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00 (1.00\u0026ndash;1.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosis: IBS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.73 (0.47\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosis: Indeterminate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.08 (0.77\u0026ndash;1.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosis: Microscopic colitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.40 (0.11\u0026ndash;1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable S1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePercent Distribution of Fecal Calprotectin Categories by Diagnosis.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u0026ndash;119\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120\u0026ndash;249\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e250\u0026ndash;499\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;500\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIBD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e27.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIBS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndeterminate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicroscopic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable S2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary by Diagnostics. Descriptive statistics of fecal calprotectin (\u0026micro;g/g) across diagnostic categories.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003emean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003esd\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003emin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003emedian\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIBD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e418\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e556\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIBS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndeterminate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e97.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e199\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicroscopic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e352\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable S3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDiagnostic performance of fecal calprotectin thresholds Positive\u0026thinsp;=\u0026thinsp;IBD, Negative\u0026thinsp;=\u0026thinsp;IBS\u0026thinsp;+\u0026thinsp;Indeterminate\u0026thinsp;+\u0026thinsp;Microscopic.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCutoff (\u0026micro;g/g)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSensitivity (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSpecificity (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePPV (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNPV (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e80.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e35.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e44.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e73.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e56.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e70.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e55.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e71.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e146\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e47.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e77.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e58.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e69.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e34.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e88.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e66.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e67.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable S4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFecal calprotectin boxplot and P values across infection status and phenotype.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhenotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfection\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP_value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMicroscopic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneral infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e424\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIBS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneral infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.947\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.947\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIBD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneral infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e794\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.968\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.968\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIndeterminate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneral infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.694\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.694\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable S5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFecal calprotectin boxplot values across infection type and phenotype.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhenotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInfection\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIQR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMicroscopic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC diff\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e110.425\u0026ndash;351.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneral infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e293\u0026ndash;424.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e145\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49.5\u0026ndash;154.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e238\u0026ndash;377\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eURI (Viral)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e138.425\u0026ndash;365.475\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUTI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e348\u0026ndash;348\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIBS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC diff\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.7\u0026ndash;37.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGI Parasite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.55\u0026ndash;45.375\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneral infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.9\u0026ndash;34.45\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.7\u0026ndash;39.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.85\u0026ndash;32.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eURI (Viral)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.075\u0026ndash;31.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUTI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.7\u0026ndash;34.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIBD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC diff\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.25\u0026ndash;788\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCNS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e746\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e514\u0026ndash;978\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGI Parasite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43\u0026ndash;75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneral infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55.6\u0026ndash;794.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e117\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61.2\u0026ndash;759\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.3\u0026ndash;585\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eURI (Viral)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e67.425\u0026ndash;727.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUTI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.65\u0026ndash;543\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIndeterminate\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC diff\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58\u0026ndash;248\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCNS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e69.1\u0026ndash;82.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGI Parasite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e128\u0026ndash;449\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGeneral infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54\u0026ndash;278\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e61\u0026ndash;227.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60.1\u0026ndash;324\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eURI (Viral)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55.8\u0026ndash;280\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUTI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54.225\u0026ndash;171.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable S6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable logistic regression with calprotectin categories. Outcome: Infection within 36 months. Reference groups: Calprotectin\u0026thinsp;\u0026lt;\u0026thinsp;50 \u0026micro;g/g, Diagnosis: IBD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds Ratio (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalprotectin 50\u0026ndash;149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.63 (0.41\u0026ndash;0.97)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.037\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalprotectin 150\u0026ndash;249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.96 (0.52\u0026ndash;1.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalprotectin 250\u0026ndash;499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.91 (0.52\u0026ndash;1.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalprotectin\u0026thinsp;\u0026ge;\u0026thinsp;500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.95 (0.58\u0026ndash;1.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosis: IBS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.62 (0.38\u0026ndash;1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosis: Indeterminate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.12 (0.80\u0026ndash;1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosis: Microscopic colitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.41 (0.11\u0026ndash;1.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable S7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eROC analysis of fecal calprotectin for infection prediction by diagnosis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiagnosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIBD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.52 (0.45\u0026ndash;0.59)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIBS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.49 (0.39\u0026ndash;0.60)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndeterminate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.52 (0.45\u0026ndash;0.59)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicroscopic colitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.81 (0.50\u0026ndash;1.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eFecal calprotectin (FC) levels differed substantially across diagnostic categories. Patients with IBD (n\u0026thinsp;=\u0026thinsp;249) had the highest mean fecal calprotectin concentration (418 \u0026micro;g/g, SD 541), followed by microscopic colitis (n\u0026thinsp;=\u0026thinsp;12; mean 203 \u0026micro;g/g, SD 156) and indeterminate (n\u0026thinsp;=\u0026thinsp;261; mean 157 \u0026micro;g/g, SD 156). In contrast, patients with IBS (n\u0026thinsp;=\u0026thinsp;108) demonstrated markedly lower values, with a mean FC of 25.6 \u0026micro;g/g (SD 20.4). These distributions illustrate a clear inflammatory gradient, with progressively higher FC concentrations observed from IBS to indeterminate disease, microscopic colitis, and topped with IBD. These values generally align with the trends found in literature. In a study with 30 patients with IBS, they reported a mean FC level of 38.2\u0026thinsp;\u0026plusmn;\u0026thinsp;14.6 \u0026micro;g/g [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Both our findings and those of the literature can be mechanistically explained as the lack of autoimmune intestinal inflammation seen in IBS as opposed to IBD. In regard to indeterminate colitis, literature currently lacks consensus on typical FC values. The third level of the gradient, microscopic colitis, was reported by a meta analysis to have a mean FC level of 214.3\u0026thinsp;\u0026plusmn;\u0026thinsp;176.7 \u0026micro;g/g [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Even with a smaller n value, in comparison of our microscopic colitis cohort to that of literature, they share a similar numerical basis. Lastly, in a study of 93 patients with active IBD the mean FC level was 906.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1,484.9 \u0026micro;g/g in UC and 1,054.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1,252.5 \u0026micro;g/g in Crohn\u0026rsquo;s. In those with mucosal healing, that study reported mean FC levels of 85.5\u0026thinsp;\u0026plusmn;\u0026thinsp;55.6 \u0026micro;g/g [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Our study reported an average FC of 418 \u0026micro;g/g\u0026thinsp;\u0026plusmn;\u0026thinsp;541\u0026micro;g/g in the 249 patients with IBD, with no discrimination between active and controlled disease.\u003c/p\u003e \u003cp\u003eFurthermore, previous research has shown that patients with \u003cem\u003eC. diff\u003c/em\u003e infection have significantly higher levels of fecal calprotectin (FC) compared to the FC levels of healthy patients. When \u003cem\u003eC. diff\u003c/em\u003e was compounded with a concomitant UC diagnosis the FC was higher than that of UC patients without \u003cem\u003eC. diff.\u003c/em\u003e That said, no diagnostic threshold was established\u003csup\u003e15\u003c/sup\u003e. That study also examined the impact of mild vs severe \u003cem\u003eC. diff\u003c/em\u003e infection and yielded a sensitivity and specificity of 57% and 88% for non-severe \u003cem\u003eC. diff\u003c/em\u003e infection and mild \u003cem\u003eC. diff\u003c/em\u003e infection respectively [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. On the contrary, our study did not find significant increases in FC following \u003cem\u003eC. diff\u003c/em\u003e when combined with concomitant diagnoses such as UC.\u003c/p\u003e \u003cp\u003eMoreover, SARS-CoV-2 infection has shown elevated levels of FC\u003csup\u003e8\u003c/sup\u003e as well as increased the number of gut brain interaction disorders from pre-pandemic to post pandemic [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The aforementioned studies indicated elevated FC levels but lacked specification of differences in FC during infection and post infection. Our data suggests that infection blurs the line of our moderate range fecal calprotectin levels especially in IBD and Indeterminate where the 250 \u0026micro;g/g range had similar values between infection and non-infection (Table S5), but overall upper respiratory infections do not significantly impact already diagnosed conditions.Thereforecaution should be used in the presence of infection during clinical evaluation of GI symptoms. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e consequently suggests a framework for proceeding after FC levels have been pulled and there is suspicion for a concomitant infection.\u003c/p\u003e \u003cp\u003eAdditionally, in a study of 84 patients, concentrations of FC in patients with positive bacterial stool cultures were significantly elevated compared with those with positive viral stool studies [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. When we stratified by specific infection subtype, FC values for common infections, including viral upper respiratory and urinary tract infections, demonstrated substantial overlap with those of patients without infection, with no statistically significant differences observed (Table S4). The lack of statistical significance in this portion of our study may be attributed to the larger allotted time for infection and allowance of multiple infection subtypes per FC level.\u003c/p\u003e \u003cp\u003eLastly, our findings highlight that while FC remains a highly useful marker for identifying inflammatory bowel disease, concurrent infections confounds diagnostic accuracy. In clinical practice, borderline FC elevations (100\u0026ndash;300 \u0026micro;g/g) in recently infected patients should be interpreted cautiously and often warrant retesting after resolution of infection. Across this large, heterogeneous outpatient cohort, FC reliably differentiated IBD from non-IBD conditions, with predictable improvements in specificity as diagnostic thresholds increased. Infection modestly elevated FC across all diagnoses, but the magnitude of increase was substantially smaller than that observed in true intestinal inflammation. These findings emphasize: FC retains diagnostic value in the presence of infection, though thresholds may require careful contextual interpretation, and indeterminate and borderline FC values (50\u0026ndash;250 \u0026micro;g/g) represent the greatest interpretive challenge, particularly when concurrent infection is present. Based on these findings, we propose a pragmatic clinical framework in which infection status primarily modifies interpretation of borderline fecal calprotectin values, while higher thresholds retain diagnostic specificity for IBD (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this large, real-world outpatient cohort, FC demonstrated a clear and progressive gradient across gastrointestinal phenotypes, with the lowest values observed in IBS and the highest in IBD. Fecal calprotectin remained a useful tool for distinguishing inflammatory from non-inflammatory disease; however, its diagnostic performance was meaningfully influenced by concurrent or recent infection. Infection was associated with modest elevation of FC across all diagnostic groups, reducing specificity at lower thresholds and contributing to diagnostic uncertainty, particularly within the borderline range of 50\u0026ndash;250 \u0026micro;g/g. Higher FC thresholds were associated with improved specificity and overall diagnostic accuracy, even among infected patients, supporting threshold escalation as a pragmatic strategy in complex clinical settings. These findings underscore the importance of contextual interpretation of FC results. In patients with recent infection, borderline elevations should be interpreted cautiously and may warrant repeat testing after infection resolution rather than immediate escalation to invasive evaluation. Overall, FC remains a valuable biomarker when integrated with clinical context, infection history, and diagnostic uncertainty. Future prospective studies should examine the impact of infection timing, antibiotic exposure, and incorporation of complementary clinical and laboratory markers to further refine diagnostic pathways and reduce indeterminate classifications.\u003c/p\u003e \u003cp\u003eThis study has several important limitations. First, although the cohort was prospectively assembled, infection status was determined through electronic medical record documentation, which may be subject to incomplete capture or variable timing relative to FC collection. The 36-month infection window likely includes both remote and recent infections, limiting the ability to precisely attribute FC elevations to active or resolving infectious processes at the time of testing. Second, the indeterminate diagnostic category reflects real-world clinical uncertainty but is inherently heterogeneous; some patients were later reclassified, which may have introduced misclassification bias despite our decision to analyze FC values based on diagnosis at the time of testing. Third, FC assays were obtained as part of routine clinical care, and potential variability related to sample handling, timing relative to symptom onset, or assay-specific factors could not be fully controlled. Extreme FC values demonstrated wide dispersion, reflecting real-world biological variability but also contributing to overlap between diagnostic groups. Finally, this analysis focused on FC as a standalone biomarker. Other clinically relevant variables such as symptom duration, inflammatory blood markers, antibiotic exposure, and treatment status were not incorporated into multivariable models. As a result, the findings should be interpreted as reflective of FC performance in isolation rather than as part of a comprehensive diagnostic algorithm.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflicts of Interest\u003c/h2\u003e \u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthics\u003c/h2\u003e \u003cp\u003e The study was approved by the Institutional Review Board University of Illinois College of Medicine at Peoria 2356668-3. All authors comply with the journal's ethical policies.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe author has nothing to report.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization, EB, DH, MS, AD, JF.; Methodology, EB, JF, MS, AD.; Validation, EB, JF, MS, AD, BO, DH.; Investigation, EB, BO, MS, DH, AD.; resources, JF.; data curation, EB.; writing\u0026mdash;original draft preparation, EB, and LW..; writing\u0026mdash;review and editing, EB, and LW; supervision, EB., JF.; project administration, EB,. JF. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRamos GP, Papadakis KA. (2019). 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Am J Emerg Med. 2015;33(10):1436\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ajem.2015.07.007\u003c/span\u003e\u003cspan address=\"10.1016/j.ajem.2015.07.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSupplemental.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Fecal Calprotectin1, IBD2, IBS3, Infection4, Indeterminate Colitis5","lastPublishedDoi":"10.21203/rs.3.rs-8576222/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8576222/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDistinguishing inflammatory bowel disease (IBD) from post-infectious or functional gastrointestinal symptoms remains challenging. Fecal calprotectin (FC) is widely used to differentiate inflammatory from non-inflammatory disease, yet real-world performance in the context of infectious comorbidity and indeterminate presentations remains incompletely characterized.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA prospective cross-sectional analysis of 702 adults undergoing FC testing within a tertiary-care gastroenterology (GI) network (September\u0026ndash;December 2024) was performed to evaluate the influence of recent infection on FC interpretation and diagnostic classification. Classifications included IBD, irritable bowel syndrome (IBS), microscopic colitis, and indeterminate. FC distributions were compared using Kruskal\u0026ndash;Wallis testing with Dunn\u0026rsquo;s correction. Diagnostic performance for identifying IBD was assessed at standard thresholds (\u0026ge;\u0026thinsp;50, 150, 250, and 500 \u0026micro;g/g) with infection stratification.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003ePatient stratification by FC resulted in 39.7% confirmed IBD, 16.9% IBS, 41.6% Indeterminate, and 1.7% microscopic colitis. Graded FC values followed: IBS\u0026thinsp;\u0026lt;\u0026thinsp;Microscopic\u0026thinsp;\u0026lt;\u0026thinsp;Indeterminate\u0026thinsp;\u0026lt;\u0026thinsp;IBD; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Median FC was lowest in IBS (19.6 \u0026micro;g/g) and highest in IBD (219 \u0026micro;g/g). Infection was documented in 55% of patients and was associated with modest FC elevation across diagnoses. Diagnostic specificity improved with increasing FC thresholds, rising from 35.7% at \u0026ge;\u0026thinsp;50 \u0026micro;g/g to 88.7% at \u0026ge;\u0026thinsp;500 \u0026micro;g/g. Infection reduced specificity at lower thresholds, with greatest interpretive uncertainty from 50\u0026ndash;250 \u0026micro;g/g.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFC remains a valuable biomarker for distinguishing inflammatory from non-inflammatory disease alongside simultaneous infectious consideration. Borderline FC elevations require cautious interpretation in post-infectious settings, with repeat testing after infection resolution.\u003c/p\u003e","manuscriptTitle":"Diagnostics of Fecal Calprotectin Across Gastrointestinal Diagnoses With Presence of Infection","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-16 15:05:27","doi":"10.21203/rs.3.rs-8576222/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a6695a25-0c60-43f8-8f0d-d9c2260e0fe8","owner":[],"postedDate":"January 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-18T16:56:03+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-16 15:05:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8576222","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8576222","identity":"rs-8576222","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}