A case for improved assessment of gut permeability – a meta-analysis quantifying the lactulose:mannitol ratio in coeliac and Crohn’s disease

A case for improved assessment of gut permeability – a meta-analysis quantifying the lactulose:mannitol ratio in coeliac and Crohn’s disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research article A case for improved assessment of gut permeability – a meta-analysis quantifying the lactulose:mannitol ratio in coeliac and Crohn’s disease Jonathan Gan, Scarlet Nazarian, Julian Teare, Ara Darzi, Hutan Ashrafian, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-257838/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Jan, 2022 Read the published version in BMC Gastroenterology → Version 1 posted 4 You are reading this latest preprint version Abstract Background A widely used method in assessing small bowel permeability is the lactulose:mannitol test, where the lactulose:mannitol ratio (LMR) is measured. However, there is discrepancy in how the test is conducted and in the values of LMR obtained across studies. This meta-analysis aims to determine LMR in healthy subjects, coeliac and Crohn’s disease. Methods A literature search was performed using PRISMA guidance to identify studies assessing LMR in coeliac or Crohn’s disease. 19 studies included in the meta-analysis measured gut permeability in coeliac disease, 17 studies in Crohn’s disease. Outcomes of interest were LMR values and comparisons of standard mean difference (SMD) and weighted mean difference (WMD) in healthy controls, inactive Crohn’s, active Crohn’s, treated coeliac and untreated coeliac. Pooled estimates of differences in LMR were calculated using the random effects model. Results Pooled LMR in healthy controls was 0.014 (95% CI: 0.006–0.022) while pooled LMRs in untreated and treated coeliac were 0.133 (95% CI: 0.089–0.178) and 0.037 (95% CI: 0.019–0.055). In active and inactive Crohn’s disease, pooled LMRs were 0.093 (95% CI: 0.031–0.156) and 0.028 (95% CI: 0.015–0.041). Significant differences were observed in LMR between: (i) healthy controls and treated coeliacs (SMD = 0.409 95% CI 0.034 to 0.783, p = 0.032), (ii) healthy controls and untreated coeliacs (SMD = 1.362 95% CI: 0.740 to 1.984, p < 0.001), (iii) treated coeliacs and untreated coeliacs (SMD = 0.722 95% CI: 0.286 to 1.157, p = 0.001), (iv) healthy controls and inactive Crohns (SMD = 1.265 95% CI: 0.845 to 1.686, p < 0.001), (v) healthy controls and active Crohns (SMD = 2.868 95% CI: 2.112 to 3.623, p < 0.001), and (vi) active Crohns and inactive Crohns (SMD = 1.429 (95% CI: 0.580 to 2.278, p = 0.001). High heterogeneity was observed, which was attributed to variability in protocols used across different studies. Conclusion The use of gut permeability measurements in screening and monitoring of coeliac and Crohn’s disease is promising. LMR is useful in performing this function with significant limitations. More robust alternative tests with higher degrees of clinical evidence are needed if measurements of gut permeability are to find widespread clinical use. Trial Registration Not Applicable Gastroenterology & Hepatology Coeliac Crohn’s Disease Lactulose Mannitol test Gut Permeability Figures Figure 1 Figure 2 Figure 3 Background There is emerging evidence that disturbances in gut barrier function play an important role in gastrointestinal (GI) diseases such as coeliac disease, inflammatory bowel disease (IBD), environmental enteric dysfunction, and in conditions outside the GI tract such as schizophrenia, autism and Parkinsons Disease 1 – 2 . Current established methods of measuring gut permeability in patients include the lactulose:mannitol (L:M) test, lactulose:rhamnose (L:R) test, chromium-51 labelled ethylenediamine tetraacetic acid (Cr-EDTA) assay, polyethylene glycol (PEG) test, use of Ussing chambers, analysis of haematological markers such as zonulin, and analysis of bacterial markers such as systemic lipopolysaccharide (LPS) 2 . Despite the various options available to measure gut permeability, their use in clinical settings is still limited 2 . For the practising clinician, a reliable gut permeability assay could potentially provide a new way to monitor established diseases such as IBD and coeliac disease, and to develop a better understanding of functional gut disorders (FGDs). FGD is currently used as a ‘catch-all’ term for poorly understood gastrointestinal conditions and treated as a diagnosis of exclusion. The impact of FGD on health systems is not to be underestimated. Globally, it affects 11% of the population and accounts for 20–50% of gastroenterology outpatient work 3 . A better appreciation of the link between gut permeability and FGD would aid the clinician in tackling this multi-faceted condition in a more effective manner. One of the widely used methods to measure small bowel permeability is the L:M test, in which, after a period of fasting, subjects are asked to drink a solute containing the two sugars lactulose and mannitol. Urinary excretion of both lactulose and mannitol are then measured several hours after ingestion of solute, and the lactulose:mannitol ratio (LMR) is calculated as an indicator of permeability 4 . The L:M test is useful as both sugars are passively absorbed from the intestine, not extensively metabolised, and excreted unchanged in urine in proportion to the quantities absorbed 4 . The smaller sugar alcohol molecule (mannitol) is assumed to permeate transcellularly through the water pores of the membrane, whereas the larger disaccharide molecule (lactulose) is assumed to permeate paracellularly through the tight junctions 5 . In states of increased gut permeability, lactulose would traverse through the paracellular spaces, cleared by glomerular filtration, not undergo selective reabsorption, and present itself in higher levels in urine, thus leading to an increased LMR. The L:M test is thought to be a good representative of gut permeability as measurements using a single molecule do not account for confounding factors such as intestinal transit time, gastric emptying rate, renal/hepatic function or total urinary excretion 6 . By taking the ratio of excretion of two molecules, the effects of these confounding factors can be eliminated 7 . Although the L:M test has been in use since the 1970s 8 , it suffers from limitations, particularly in subjects where longitudinal urine collection is challenging (e.g. infants 9 and patients with reduced urinary output 10 ). Furthermore, absolute LMR values for the small bowel in healthy subjects and in disease are not yet established. To address this issue, we performed a meta-analysis to quantify LMR values in healthy participants and in various states of coeliac and Crohn’s disease, two conditions in which altered gut permeability is observed. The results of this meta-analysis are presented below, and variations in the methods used to conduct the L:M test are also explored. To the best of our knowledge, there are not many meta-analyses presented on the L:M test in coeliac and Crohn’s disease. The results highlight the limitations of the test and the improvements required to bring measurements of gut permeability into larger scale clinical use. Methods A systematic review was conducted according to the recommendations in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement 11 . Prior to conducting the meta-analysis, the eligibility criteria, description of intervention, and comparison and outcome of interest were established. The literature search was conducted by two independent reviewers. Eligibility criteria We included all observational studies, cross-sectional studies, cohort studies and trials pertaining coeliac and Crohn’s disease. We excluded papers that did not report absolute LMR values as well as in vitro studies, animal studies, and studies where sample groups were mixed (e.g. Crohn’s plus ulcerative colitis). Studies had to be published in peer reviewed journals and the search was not restricted by language. Literature identification In January 2020, with the help of a medical librarian, literature searches were conducted using the following databases: Embase (1988–2020); Ovid MEDLINE In Process & Other Non-Indexed Citations and Ovid MEDLINE (1946 to Present); and Cochrane Database of Systematic Reviews. Terms and/or abbreviations to describe coeliac, Crohn’s disease and gut permeability were combined into a search strategy textbox. Free-text terms were then used in various combinations to ensure a complete search in the databases mentioned above. The combined searches relating to gut permeability in coeliac and Crohn’s disease were explored using the terms ‘and’ and 'or’. The following search terms were used: ‘‘permeability’’, ‘‘leaky or leakiness’’, ‘‘lactulose mannitol’’, ‘‘inflammatory bowel disease or IBD’’, ‘Crohn’s Disease’, ‘coeliac disease’, ‘Crohn’s’’, and ‘‘coeliac’’. Study selection The titles and abstracts of the search were then screened. Full text articles or abstracts of potentially relevant references in the articles also underwent review. Conference abstracts and papers with no full texts available were excluded. The study selection process was performed by two independent reviewers who were blinded (JG and SN), and any disagreements were resolved by a third author (HA). JG and SN appraised quality independently. Data extraction The following information was extracted from the studies chosen by JG and SN: number of patients, study objectives, study methodology, results, type of population, L:M study protocol, type of solute given to subjects, urine collection time, method of urine analysis and LMR values. Data extracted were then tabulated in Microsoft Excel and the study outcomes were reviewed by a third reviewer (AT). The primary study outcomes were Standardised Mean Differences (SMD) of LMR values in healthy controls, treated coeliac patients, untreated coeliac patients, patients with active Crohn’s disease, and patients with inactive Crohn’s disease. The secondary outcomes were comparisons of use of different concentrations of lactulose and mannitol (5 parts lactulose to 2 parts mannitol, and 2 parts lactulose to 1 part mannitol) in the aforementioned groups. Risk of bias assessment Randomised control trials (RCTs) were assessed using the Jadad score 12 , while non-randomised trials were assessed using the Risk Of Bias In Non-randomised Studies of Interventions tool (ROBINS-I) 13 . The Newcastle Ottawa Score (NOS) was used for cohort and case control studies 14 . The risk of bias in all studies was assessed by two independent reviewers. The parameters assessed in cohort and case control studies included study design, outcome measurements, representativeness of cases, control selections, ascertainment of exposure, and follow up rate. Using the ROBINS-I assessment tool, potential bias was assessed pre-intervention, at intervention and post intervention. For studies assessed using the NOS or the Jadad score, a single bias value was calculated for each study. In the NOS assessment, a score of ≤ 3 indicates poor quality, 4–6 moderate quality, and ≥ 7 good quality. Under the Jadad scoring system, good studies will score ≥ 3, and poor studies will score < 3. The ROBINS-I tool ranks the risk of bias in studies as ‘low risk’, ‘moderate risk’,’serious risk’, ‘critical risk’ or ‘no information’. The findings from the two assessors were evaluated by a third reviewer. Risk of bias was also assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool 15 . The tool consists of four domains: patient selection, index test, reference standard, and flow of timing. Each domain is assessed in terms of risk of bias. The first three domains are also assessed in terms of applicability to clinical practice. All three modes of assessment were performed by J.G and S.N, and any disagreements were resolved by consensus and discussion with the other authors. Statistical analysis Stata 15 (StataCorp, College Station, Texas) was used for the statistical analysis reported in this study. All analyses were performed using a random effects model in response to expected heterogeneity of data collected. In order to calculate weighted mean and standard mean values of LMR, values of LMR reported in individual studies were pooled into healthy controls, patients with untreated coeliac disease, patients with treated coeliac disease, patients with active Crohn’s and patients with inactive Crohn’s disease. The definition of active Crohn’s and inactive Crohn’s in individual papers are listed in Table S1. The Weighted Mean Difference (WMD) and Standard Mean Difference (SMD) of LMR were calculated between controls and treated coeliac, controls and untreated coeliac, treated and untreated coeliac, controls and inactive Crohn’s disease, controls and active Crohn’s disease, and active and inactive Crohn’s disease. This approach calculated overall weighted mean and standard mean differences (i.e. incorporating all relevant studies included in this meta-analysis) and also ascribed an individual weighted mean and standard mean difference for each individual study with 95% Confidence Intervals (CIs). The weighted mean differences refer to the pooled estimates, with the 'weighted' component referring to the different weights applied to each study (or each patient/participant group) in the overall calculation. This was done to accommodate the different sizes (participant number) of studies included in this meta-analysis and the different sizes of patient/participant groups within studies. Weighted mean differences and weighted mean values were calculated in line with principles set out by Egger et al 16 . Meta-analysis of summary estimates of proportions was also calculated for overall LMRs and sensitivities and specificities. All results for pooled estimates were presented with 95% CIs. I 2 values were calculated to assess heterogeneity. P values were calculated using the chi-squared test, and the results were considered significant for P < 0.05. We note that for studies in which paired data were reported (i.e. where LM ratios were measured before and after treatment), pre- and post-treatment LMR values were simply allocated into the appropriate groups (i.e. paired data was not treated differently to unpaired data). A bivariate model for diagnostic meta-analysis was used to compute pooled sensitivity and specificity data where available. The relationship between sensitivity and specificity was assessed using a hierarchical summary receiver operating characteristic (SROC) model. SROC curves were utilized to convey the diagnostic test performance and a prediction region curve was also plotted. Trapezoidal integration was used to calculate the pooled area under the curve (AUC), where 0.5 implies that a test was equally likely to diagnose a positive result as either positive or negative and a value of 1.0 indicates a ‘perfect’ test that gives a 100% correct diagnosis. A pooled AUC value of 0.75 or above represents a test with good accuracy 17 . The ‘gold standard’ test that we used for the sensitivity and specificity assessment was intestinal biopsy. Results Search results and study description After performing general searches for the relevant subjects and combining them, 377 abstracts were extracted from Medline, 569 abstracts were found in Embase and 190 in the Cochrane. After duplicates were removed, we found that the total number of relevant abstracts was 633. 50 abstracts were found to be relevant to coeliac disease. Of these, a further 31 studies were excluded as per the exclusion criteria discussed above, meaning that a total of 19 coeliac disease studies were selected for analysis. We found that 97 studies were relevant to Crohn’s disease. Of these, 80 studies were excluded according to the exclusion criteria discussed above. Hence, a total of 17 Crohn’s disease studies were included in this meta-analysis. These results are summarised in the PRISMA flow diagrams (Fig S1 and S2). The selected studies pertaining gut permeability in Crohn’s disease and coeliac disease are tabulated in Tables S1 and S2 respectively 18 – 51 . Altogether, there were 15 studies that investigated gut permeability in Crohn's disease specifically using the L:M test, 17 studies that investigated gut permeability in coeliac disease specifically using the L:M test, and 2 studies that investigated both Crohn’s and coeliac using the L:M test. Meta-analysis of results The median LMR values, and weighted and standard mean difference values calculated for each study are presented in Tables 1 and 2 . In studies where the median LMR value was unavailable, the mean value was used. Standard deviation values associated with each LMR presented in Tables 1 and 2 were either as stated in the individual studies, or if unavailable, were derived from the published range, interquartile range (IQR), 95% CI or standard error of mean (SEM) using established statistical methods 52 – 53 . Table 1 Summary of number (no) of patients/participants and lactulose:mannitol ratios (LMRs) reported in untreated coeliac patients, treated coeliac patients, and healthy controls. Where appropriate data was available, the calculated weighted mean difference (WMD) and standard mean difference (SMD) in LMR (between the coeliac cohort and healthy controls) are also shown. *=mean value, **=unknown if value is mean or median, …=Standard deviation (SD) calculated from range, ……=SD calculated from interquartile range (IQR), ………=SD calculated from standard error of mean (SEM), …………=SD calculated from 95% confidence interval (CI). Study Outcome No of healthy controls Reported LMR in healthy controls Standard Deviation No of untreated coeliac patients Reported LMR in untreated coeliac Standard Deviation No of treated coeliac patients Reported LMR in treated coeliac patients Standard Deviation Statistically calculated WMD (95% CI) Statistically calculated SMD (95% CI) Elia et al 1991 Control vs untreated coeliac 24 0.021* 0.020 ……… 15 0.152* 0.120 ……… 0.131 (0.070, 0.192) 1.736 (0.979, 2.492) Vogelsang et al 2001 Treated vs untreated coeliac 16 0.12 0.058 … 19 0.028 0.028 … 0.092 (0.061, 0.123) 2.085 (1.252, 2.919) Kuitunen et al 1996 Control vs untreated coeliac 18 0.030 0.043 … 22 0.260 0.410 … 0.230 (0.058, 0.402) 0.751 (0.106, 1.397) Kuitunen et al 1996 Control vs treated coeliac 18 0.030 0.043 … 17 0.040 0.010 … 0.010 (-0.010, 0.030) 0.316 (-0.351, 0.983) Kuitunen et al 1996 Treated vs untreated coeliac 22 0.260 0.410 … 17 0.040 0.010 … 0.220 (0.049, 0.391) 0.712 (0.059, 1.365) Ukabam et al 1985 Control vs untreated coeliac 25 0.009 0.003 … 13 0.110 0.156 … 0.101 (0.016, 0.186) 1.121 (0.402, 1.839) Ukabam et al 1985 Control vs treated coeliac 25 0.009 0.003 … 13 0.016 0.016 … 0.007 (-0.002, 0.016) 0.728 (0.037, 1.419) Ukabam et al 1985 Treated vs untreated coeliac 13 0.110 0.156 … 13 0.016 0.016 … 0.094 (0.009, 0.179) 0.848 (0.042, 1.653) Vilela et al 2008 Control vs treated coeliac 15 0.003 0.003 … 22 0.013 0.016 … 0.010 (0.003, 0.017) 0.785 (0.103, 1.466) Hamilton et al 1987 Control vs untreated coeliac 33 0.036 0.021 … 4 0.296* 1.308 … 0.264 (-1.018, 1.546) 0.688 (-0.362, 1.739) Marsilio et al 1998 Control vs untreated coeliac 30 0.024* 0.006 10 0.072* 0.025 0.048 (0.032, 0.064) 3.623 (2.539, 4.708) Van Elburg et al 1993 Control vs untreated coeliac 22 0.043* 0.030 ……… 9 0.243* 0.100 ……… 0.200 (0.133, 0.267) 3.425 (2.251, 4.599) Rajani et al 2016 Control vs untreated coeliac 26 0.022 0.016 … 65 0.043 0.070 … 0.021 (0.003, 0.039) 0.351 (-0.106, 0.809) Rajani et al 2016 Control vs treated coeliac 26 0.022 0.016 … 47 0.024 0.077 … 0.002 (-0.021, 0.025) 0.032 (-0.447, 0.511) Rajani et al 2016 Treated vs untreated coeliac 65 0.043 0.070 … 47 0.024 0.077 … 0.019 (0.009, 0.047) 0.261 (0.155–0.638) Smecuol et al 1997 Treated vs untreated coeliac 27 0.360* 0.380 ………… 15 0.130* 0.188 ………… 0.230 (0.058, 0.402) 0.706 (0.056, 1.356) Smecuol et al 2005 Control vs untreated coeliac 30 0.017* 0.040 ……… 30 0.073* 0.090 ……… 0.056 (0.021, 0.091) 0.804 (0.277, 1.331) Juby et al 1989 Control vs untreated coeliac 12 0.016* 0.007 ……… 17 0.163* 0.313 ……… 0.147 (-0.002, 0.296) 0.610 (-0.147, 1.367) Novacek et al 1999a Untreated coeliac disease with normal liver function tests 106 0.110 0.315 … Novacek et al 1999b Untreated coeliac disease with abnormal liver function tests before vs after gluten free diet 72 0.340 1.400 … 64 0.050 0.070 … 0.290 (0.034, 0.614) 0.284 (0.054, 0.623) Vecsei et al 2009 Treated vs untreated coeliac 47 0.177 47 0.053 Johnston et al 2000 Control vs untreated coeliac 21 0.013* 16 0.105* Johnston et al 2000 Control vs treated coeliac 21 0.013* 7 0.013* Johnston et al 2000 Treated vs untreated coeliac 16 0.105* 7 0.013* Catassi et al 1997 Control vs untreated coeliac 54 0.014 29 0.038 Smecuol et al 1999 Untreated coeliac disease 12 0.101 0.069 ………… Smecuol et al 2013a Untreated coeliac disease 10 0.110 0.159 … Smecuol et al 2013b Untreated coeliac disease 12 0.054 0.440 … Gatti et al 2013a Treated coeliac disease 75 0.055 0.04 …… Gatti et al 2013b Treated coeliac disease 96 0.052 0.055 …… Table 2 Summary of number (no) of patients/participants and lactulose:mannitol ratios (LMRs) reported in patients with active Crohn’s disease, patients with inactive Crohn’s disease, and healthy controls. Where appropriate data was available, the calculated weighted mean difference (WMD) and standard mean difference (SMD) in LMR (between the Crohn’s cohort and healthy controls) are also shown. *=mean value, **=unknown if value is mean or median, …=Standard deviation (SD) calculated from range, ……=SD calculated from interquartile range (IQR), ………=SD calculated from standard error of mean (SEM), …………=SD calculated from 95% confidence interval (CI). Study Outcome Number of healthy controls Reported LMR in healthy controls Standard deviation Number of active Crohn’s patients Reported LMR in active Crohn's Standard deviation Number of inactive Crohn’s patients Reported LMR in inactive Crohn's Standard deviation Statistically calculated WMD (95% CI) Statistically calculated SMD (95% CI) Marsilio et al 1998 Control vs active Crohn’s 30 0.024* 0.006 10 0.200* 0.082 0.176 (0.125, 0.227) 4.373 (3.157, 5.589) Vilela et al 2008 Control vs inactive Crohn’s 15 0.003 0.003 … 31 0.021 0.006 … 0.018 (0.015, 0.021) 3.467 (2.516, 4.418) Dastych et al 2008 Control vs active Crohn’s 20 0.012* 0.008 20 0.076* 0.037 0.064 (0.047, 0.081) 2.396 (1.575, 3.217) D'Inca et al 2006 Control vs inactive Crohn’s vs first degree relatives 35 0.01 0.003 … 115 0.03 0.045 … 0.020 (0.012, 0.028) 0.506 (0.123, 0.889) Wild et al 2003 Control vs inactive Crohn’s patients after 10 weeks of tapering steroids who eventually relapsed 23 0.021* 0.004 11 0.055* 0.018 0.05 (0.04, 0.07) 3.209 (2.144, 4.274) Wild et al 2003 Control vs inactive Crohn’s patients after 10 weeks of tapering steroids who eventually did not relapse 23 0.021* 0.004 11 0.026* 0.017 0.497 (-0.232, 1.225) Wild et al 2003 Control vs active Crohn’s patients 23 0.021* 0.004 30 0.088* 0.026 0.067 (0.058, 0.076) 3.387 (2.534, 4.240) Wild et al 2003 Active Crohn’s patients vs inactive Crohn’s patients after 10 weeks of tapering steroids who eventually relapsed 30 0.088* 0.026 11 0.055* 0.018 0.033 (0.019, 0.047) 1.364 (0.609, 2.118) Wild et al 2003 Active Crohn’s patients vs inactive Crohn’s patients after 10 weeks of tapering steroids who eventually did not relapse 30 0.088* 0.026 11 0.026* 0.017 0.062 (0.048, 0.076) 2.582 (1.684, 3.479) Garcia Vilela et al 2008 Control vs inactive Crohn’s 15 0.005* 0.004 31 0.021* 0.010 0.016 (0.012, 0.020) 1.879 (1.148, 2.609) Sigalet et al 2013 Control vs active Crohn’s 10 0.029* 0.008 7 0.056* 0.025 0.026 (0.007, 0.045) 1.531 (0.421, 2.641) Sigalet et al 2013 Control vs inactive Crohn’s 10 0.029* 0.008 7 0.032* 0.010 0.002 (-0.007, 0.011) 0.226 (-0.743, 1.195) Sigalet et al 2013 Active vs inactive Crohn’s 7 0.056* 0.025 7 0.032* 0.010 0.024 (0.004, 0.044) 1.261 (0.098, 2.423) Zamora et al 1999 Control vs inactive Crohn’s 21 0.019 0.01 … 14 0.027 0.040 … 0.008 (-0.013,0.030) 0.313 (-0.368, 0.993) Andre et al 1988 Control vs active Crohn’s 100 0.021* 0.01 15 0.132* 0.11 0.111 (0.055, 0.167) 2.787 (2.134, 3.440) Andre et al 1988 Control vs inactive Crohn’s 100 0.021* 0.01 15 0.074* 0.090 0.053 (0.007,0.099) 1.604 (1.023, 2.186) Andre et al 1988 Active vs inactive Crohn’s 15 0.132* 0.11 15 0.074* 0.090 0.058 (-0.014, 0.130) 0.577 (-0.154, 1.309) Sturniolo et al 2001 Inactive Crohn’s 12 0.041* 0.010 Buhner et al 2006 Control vs inactive Crohn’s vs first degree relatives vs non-blood relatives 96 0.015 0.005 …… 128 0.026 0.016 …… 0.011 (0.008, 0.014) 0.877 (0.601, 1.154) D'Inca et al 1999 Control vs Inactive Crohn’s patients who eventually relapsed 80 0.009* 0.004 52 0.045* 0.042 0.036 (0.025, 0.047) 1.359 (0.973, 1.745) D'Inca et al 1999 Control vs Inactive Crohn’s patients who eventually did not relapse 80 0.009* 0.004 78 0.027* 0.027 0.018 (0.012, 0.024) 0.938 (0.610, 1.267) Swanson et al 2011 Control vs inactive Crohn’s 7 0.094 ** 6 0.085 ** Benjamin et al 2012a Inactive Crohn’s 15 0.067 0.024 … Benjamin et al 2012b Inactive Crohn’s 15 0.071 0.061 … Hilsden et al 1996 Controls vs first degree relatives of Crohn’s patients in remission 26 0.017* 0.006 ……… Hilsden et al 1999 Inactive Crohn’s 61 0.018* 0.011 Breslin et al 2001 Controls vs spouses of patients with inactive Crohn’s 26 0.017* 0.005 ……… Pooled analysis of gut permeability results in healthy subjects analysed in 24 studies (Fig. 1 ) revealed a LMR value of 0.014 (95% CI: 0.006 to 0.022). In untreated and treated coeliac patients (Fig. 2 A & 2 B), the pooled LMR values were 0.133 (95% CI: 0.089 to 0.178) and 0.037 (95% CI: 0.019 to 0.055) respectively. In inactive Crohn’s disease (Fig. 3 A), the pooled LMR 0.028 (95% CI: 0.015 to 0.041), while in active Crohn’s disease (Fig. 3 B), the pooled LMR was 0.093 (95% CI: 0.031 to 0.156). LMR comparisons in coeliac disease The SMD and WMD in LMR between healthy controls and treated coeliac disease (4 studies) was 0.409 (95% CI: 0.034 to 0.783, p = 0.032, Fig S3A) and 0.009 (95% CI 0.003 to 0.014, p = 0.001, Fig S3B) respectively. The SMD and WMD in LMR between healthy controls and patients with untreated coeliac disease (9 studies) were calculated as 1.362 (95% CI: 0.740 to 1.984, p < 0.001, Fig S3C) and 0.090 (95% CI: 0.054 to 0.126, p < 0.001, Fig S3D) respectively. The results exhibited high heterogeneity for comparison between healthy controls and untreated coeliac (I 2 = 84.8%), but this was not the case not for the comparison between healthy controls and treated coeliac (I 2 = 31.7%). The SMD and WMD in LMR between treated and untreated coeliac disease (6 studies) were 0.722 (95% CI: 0.286 to 1.157, p = 0.001, Fig S3E) and 0.101 (95% CI: 0.040 to 0.162, p = 0.001, Fig S3F) respectively, and the results were found to be heterogenous (I 2 = 72.9%). LMR comparisons in Crohn’s disease 11 studies were included in comparisons of LMR values in Crohn’s disease. 9 studies were included in the pooled random effects analysis of LMR in healthy controls vs. inactive Crohn’s disease, revealing a SMD and WMD of 1.265 (95% CI: 0.845 to 1.686, p < 0.001, Fig S4A) and 0.017 (95% CI: 0.012 to 0.022, p < 0.001, Fig S4B) respectively. 5 studies comparing healthy controls and active Crohn’s disease were identified, showing a SMD and WMD in LMR of 2.868 (95% CI: 2.112 to 3.623, p < 0.001, Fig S4C) and 0.078 (95% CI: 0.049 to 0.107, p < 0.001, Fig S4D) respectively. High heterogeneity was observed in both comparisons (I 2 values of 85.8% and 71.8% respectively). 3 studies were included in the comparison of active and inactive Crohn’s disease, showing a SMD and WMD of 1.429 (95% CI: 0.580 to 2.278, p = 0.001, Fig S4E) and 0.042 (95% CI: 0.021 to 0.063, p < 0.001, Fig S4F) respectively, and the results were found to be heterogenous (I 2 = 74%). Subgroup comparisons using different solutes We also sought to examine if there were any differences in the results obtained when using different lactulose:mannitol ratios in the solutes given to patients during the L:M test. The solutes used in the studies cited here can be broadly divided into ratios of 5:2 (5 parts lactulose to 2 parts mannitol) and 2:1 (2 parts lactulose to 1 part mannitol). 5:2 solute used in Crohn’s and coeliac disease Using 5:2 solutes, the SMD and WMD in LMR between healthy controls and untreated coeliac disease (6 studies) were found to be 1.495 (95% CI: 0.549 to 2.441, p = 0.002) and 0.072 (95% CI: 0.033 to 0.11, p < 0.001) respectively. This was associated with high heterogeneity (I 2 = 89.6%). In treated vs untreated coeliac disease (2 studies), the SMD and WMD in LMR were 0.401 (95% CI: -0.003 to 0.806, p = 0.052) and 0.107 (95% CI: -0.097 to 0.311, p = 0.305) respectively. This was associated with low heterogeneity (I 2 = 25.6%). Only one study was found in which healthy controls were compared with treated coeliac patients using 5:2 solutes and hence no analysis was done for this. In studies comparing patients with Crohn’s disease and healthy subjects, 4 studies were found using 5:2 solutes. The SMD and WMD in LMR between inactive Crohn’s disease and healthy controls (2 studies) were 0.284 (95% CI: -0.273 to 0.841, p = 0.318) and 0.003 (95% CI: -0.005 to 0.011, p = 0.486) respectively. The heterogeneity of results was low (I 2 = 0%). The analysis of SMD and WMD in LMR between active Crohn’s disease and healthy controls (2 studies) revealed a difference 2.941 (95% CI: 0.156 to 5.725, p = 0.038) and 0.099 (95% CI: -0.048 to 0.246, p = 0.186) respectively, and the results were highly heterogeneous (I 2 = 91.3%). Only 1 study was found where inactive vs active Crohn’s was compared using the 5:2 solute and hence no analysis was done for this. 2:1 solute used in Crohn’s and coeliac disease 9 studies investigated the difference in LMR between healthy controls and coeliac disease using the 2:1 solute. Comparing healthy controls against untreated coeliac disease (4 studies), the SMD and WMD in LMR were calculated as 1.737 (95% CI: 0.701 to 2.773, p = 0.001) and 0.103 (95% CI: 0.038 to 0.167, p = 0.002) respectively. This was associated with high heterogeneity (I 2 = 85.9%). Comparing LMR in healthy controls against treated coeliac disease in 3 studies revealed a SMD and WMD of 0.604 (95% CI: 0.212 to 0.997, p = 0.003) and 0.009 (95% CI: 0.004–0.014, p < 0.0001) respectively, which was associated with low heterogeneity (I 2 = 0%). Analysis of SMD and WMD in LMR between treated and untreated coeliac patients (4 studies) revealed a difference of 0.992 (95% CI: 0.200 to 1.645, p = 0.012) and 0.103 (95% CI 0.061 to 0.144, p < 0.001) respectively, and this was associated with high heterogeneity (I 2 = 81.3%). 9 studies performed comparisons of LMR in patients with Crohn’s disease using the 2:1 solute. Analysis of 6 studies comparing SMD and WMD in healthy controls and inactive Crohn’s disease revealed a change of 1.442 (95% CI: 0.944 to 1.941, p < 0.001) and 0.018 (95% CI: 0.014–0.023, p < 0.001) respectively which was associated with high heterogeneity (I 2 = 88.3%). 3 studies were found comparing healthy controls and active Crohn’s disease, and analysis revealed SMD and WMD in LMR of 3.312 (95% CI: 2.257 to 4.366, p < 0.001) and 0.089 (95% CI: 0.056 to 0.121, p < 0.001) with high heterogeneity (I 2 = 73%). Only 1 study was found where inactive vs active Crohn’s was compared using the 2:1 solute and hence no analysis was done for this. Sensitivity and specificity analysis We analysed the sensitivity and specificity based on the available data in the papers included in our review. 4 studies reported diagnostic accuracies for the L:M test in screening for coeliac disease. The sensitivity and specificity data are presented in Table S4. Pooled specificity (Fig S5A) was calculated as 0.700 (95% CI: 0.551–0.849), and pooled sensitivity (Fig S5B) was calculated as 0.829 (95% CI: 0.682–0.976). However, the overall heterogeneity for sensitivity and specificity was high (I 2 = 94.3% and 78.4% respectively). Sensitivity and specificity values for coeliac disease were also calculated based on a SROC curve (Fig S5C). The pooled, weighted AUC was calculated as 0.88 (95% CI: 0.85–0.91). Based on the SROC graph, the estimated positive likelihood ratio was 4.0 (95% CI: 1.5–10.6) and the estimated negative likelihood ratio was 0.15 (95% CI: 0.04–0.6). The estimated diagnostic odds ratio was 27 (95% CI: 4-194). The estimated sensitivity and specificity from the SROC graph were 0.89 (95% CI: 0.62–0.97) and 0.78 (95% CI: 0.51–0.92) respectively, in agreement with the pooled results reported above. Sensitivity and specificity analysis were not performed for Crohn’s disease due to paucity of data in the studies included in our meta-analysis. Risk of bias assessment In 30 studies where the Newcastle Ottawa Score was used to assess bias, 9 studies had low risk, 20 had moderate risk, and 1 had high risk of bias. Risk of bias was assessed using the Jadad score in 4 RCT studies, and we found that 3 studies were of good quality, and 1 study was of poor quality. 5 studies were assessed using the ROBINS-I tool, and we found that 2 studies had moderate risk of bias and 3 studies had serious risk of bias. Assessment using the QUADAS-2 tool raised several methodologic limitations, such as the absence of an index test due to the heterogeneity associated with the conduct of the lactulose mannitol test (hence there are concerns about the applicability of the index test), and the difficulty in assessing if the reference standard set in each study was interpreted without the knowledge of the results of any index test performed (hence the risk of bias in the reference standard domain is ‘unknown’). The detailed assessments of bias in each domain using the Jadad score, NOS, ROBINS-1 tool and QUADAS-2 tool are described in the Supplementary material (Tables B1-B7). Discussion Overall, this meta-analysis demonstrates that despite considerable heterogeneity in the data, there are significant differences in LMR between healthy subjects and patients with either coeliac or Crohn’s disease. There are also significant differences in LMR between treated and untreated coeliac, and active compared to inactive Crohn’s disease. These results hold true even when different L:M solute ratios are used. Altogether, there were 18 studies that used a 2:1 ratio of lactulose to mannitol, and 13 studies that used a 5:2 ratio. While no previous studies have performed direct comparisons of the data obtained using different solute ratios, we found that standard mean differences in LMR were larger when using the 2:1 ratio than the 5:2 (although high heterogeneity in the data means that this observation should be taken with caution, and statistical significance was not observed). However, the numbers in each subgroup were small, which may explain the mixed significances and heterogeneities observed. Nevertheless, this raises the possibility that the heterogenous nature of our results could be attributed to the different L:M solute ratios used, along with other factors such as assay method, time of fasting before the solute is administered, and urine collection times. Musa et al. found no significant difference in LMR when comparing prolonged urine collection time (5 hours) with urine collected over a 2 hour period 54 . In the same study, they also found no significant differences when using two different analysis methods: high-performance anion exchange chromatography with derivatization-free, pulsed amperometric detection (HPAE-PAD); and liquid chromatography with tandem mass spectrometry (LC-MSMS) 54 . This concurred with results from Akram’s earlier study regarding urine collection, which found no significant differences in LMR when urine was collected over 2 and 6 hours 55 . Camilleri et al., on the other hand, found that LMR based on urine collections over 8–24 hours were significantly higher than those for collections times of 0–2 hours 6 . Interestingly, a study by Sequeira and colleagues suggested that differences in temporal patterns of excretion of lactulose and mannitol can be minimised if the urine collection period is restricted to 2½4 hours after solute ingestion 56 . In relation to analysis platforms used for quantification of urinary lactulose and mannitol, Lee et al. found that LC-MSMS provides more accurate measurements than HPAE-PAD 57 . They subsequently recommended the former to be used in L:M studies. Nonetheless, current evidence surrounding the variable protocols used in L:M studies (e.g. in terms of the analysis platforms, solute ratios and urinary collection times used) is mixed, and more studies are required to elucidate the optimal method for performing this test. Despite the variability and heterogeneity observed, we found significant differences in LMR between healthy controls and untreated coeliac disease. Patients with active coeliac disease are known to have flat mucosa, increased villous height, and increased paracellular permeability due to wider tissue junction pores and release of pro-inflammatory cytokines 58 , 59 , 60 . Gluten is thought to activate zonulin signalling, which opens up the tight junctions, causing increased paracellular permeability 61 . The role of gut permeability in the pathogenesis of coeliac disease is currently poorly understood, but it is thought that it might act to self-sustain the inflammatory response and perpetuate a vicious cycle 62 . Regardless, the increased permeability leads to an increase in lactulose excretion into urine, resulting in significantly higher LMR values than those observed in healthy subjects. Differences in LMR between treated and untreated coeliac disease were also observed and found to be significant, with the change in LMR observed across all coeliac studies included in this review. These changes need to be analysed with caution, however, as the results were heterogenous and the 95% confidence interval was fairly wide (0.029–0.218). There were also significant differences between the LMR values observed in treated coeliac disease and healthy controls, implying that it may take some time before mucosal integrity returns to baseline. A study by Cummins et al. showed (via the L:R test) that gut permeability improves after 2 months on a gluten free diet (GFD), but that it takes up to 6 months before villous recovery is observed 63 . Duerksen and colleagues demonstrated that more than 80% of coeliac patients on GFD for at least a year exhibited reduced gut permeability, although permeability only returned to normal levels in 48% of patients (10/21) 64 . Rajani et al. (one of the papers included in this analysis) reported no significant difference in LMR between healthy controls and coeliac patients who followed a GFD for a year 44 . Similarly, Vogelsang et al. (another paper included in this analysis) also reported no significant difference in LMR when comparing healthy subjects against coeliac patients who had a median of 44 months on a GFD 35 . However, LMR values were significantly different (healthy vs. treated coeliac) in the studies published by Vilela et al. (1 year of GFD) 19 and Ukabam et al. (5–8 months of GFD) 38 . Thus, current evidence points towards the role of a GFD in improving gut permeability and restoring gut integrity after more than 12 months. Another important finding in this review is the presence of significant differences in LMR between healthy controls and both active and inactive Crohn’s disease. Moreover, significant differences were also observed between active and inactive Crohn’s patients. While the pathogenesis of Crohn’s disease is multifactorial and the link to gut permeability is still not well understood, a study in 2019 using three-dimensional tissue culture models demonstrated that epithelial barrier dysfunction may be caused by Tumour Necrosis Factor (TNF)-α induced tight junction modulation and involvement of the c-Jun N-terminal protein kinase mitogen-activated protein kinases (JNK MAPK) signalling pathway 65 . Furthermore, altered gut permeability is surmised to be present at the early stages of disease, as increased paracellular permeability was found even in patients with quiescent IBD where endoscopic activity was absent 66 . Techniques other than the L:M test have also been used to assess gut permeability in Crohn’s disease. For example, in a recent study, a moderate positive correlation was found between excreted Chromium-52 labelled ethylenediamine tetraacetic acid ( 52 Cr-EDTA) and faecal calprotectin levels (a known marker of gut permeability) in Crohn’s patients 67 . Similarly, the use of zonulin 68 and Ussing chambers 69 have also demonstrated increases in gut permeability in Crohn’s disease. Thus, our findings are in agreement with the above studies and provide further evidence for the importance of gut permeability in Crohn’s disease. Interestingly, the differences in LMR between controls, active and inactive Crohn’s disease were smaller than those observed for untreated coeliac disease. This may indicate that the breakdown in epithelial barrier function is more pronounced in coeliac disease than it is in Crohn’s. Despite this, there was again significant heterogeneity in the difference values observed between control and active Crohn’s disease, and between inactive and active Crohn’s disease. This further indicates that observations made with the L:M test need to be taken with caution. There are many advantages of the L:M test in measuring gut permeability. It is easy to perform, inexpensive and non-invasive. Our data also suggests that this test is associated with high sensitivity, making it a useful tool in screening for coeliac disease. (Sensitivity and specificity analysis was not performed for Crohn’s disease as the necessary data was not available in the papers included in our review). The L:M test was the method of choice in the MAL-ED study, which investigated the link between gut permeability and environmental enteropathy in children across 8 countries 70 . However, there is great variability in how the test is performed and our meta-analysis has revealed considerable heterogeneity in the results obtained. Interestingly, Ordiz et al. – who conducted the L:M test in 1669 rural Malawian children – surmised that the strong direct correlation between percentage lactulose and percentage mannitol excretion does not support the use of mannitol as a normalising factor for lactulose, and that using percentage lactulose excretion alone actually yields more information about gut integrity than LMR 71 . In addition, L:M measurements performed by Camilleri et al. indicated that LMR at 0–2 hours may in part reflect colonic permeability and not exclusively small bowel permeability. They have hence recommended that measurements of small bowel permeability using urine collected in the L:M test over 0–6 hours should be treated with caution 72 . While there are clear limitations to the L:M test, the quantification of gut permeability in coeliac and Crohn’s disease reported here highlights a potential route for clinicians to better understand other gastrointestinal conditions where current diagnostics can be improved. For example, as larger changes in LMR were obtained in coeliac disease than in the Crohn’s disease (relative to healthy controls), this implies the possibility to stratify patients according to their gut permeability. Similarly, as differences were observed between treated and untreated patients, this suggests an opportunity to monitor for signs of relapse in a non-invasive manner (i.e. without the need for endoscopy). Thus, quantifying gut permeability may provide an avenue for the practising clinician to better assess patients with FGDs. Indeed, there is promise in utilising gut permeability values to improve management of this complex group of patients in either the primary care setting or the gastroenterology clinic. Nonetheless, we stress that the results of our meta-analysis do not necessarily suggest that the L:M test is currently suitable for this purpose. The high heterogeneity observed across groups and datasets means that it is unlikely that the L:M test will find widespread clinical use in its current form (and indeed explains why it has not done so to date). Hence, if assessment of gut permeability is to find widespread use in the diagnosis of FGDs, Crohn’s, coeliac or other conditions then it is highly likely that improved diagnostic tools/methods (or at the very least improved protocols for deployment of the L:M test) will be required. Limitations The main limitation of this meta-analysis is the heterogeneity of our results, which is likely to be explained by the variations in how the L:M test was performed (and by physiological variations across individuals). A list of protocol variations that may have caused the heterogeneity is presented in Table S3. It is also difficult to directly assess the results of the two different solutes used due to the heterogeneity in most of these comparisons. In one of the studies 18 , both 5:2 and 2:1 lactulose: mannitol ratios in the solutes were given to patients during the L:M test, making it more difficult to compare the differences in LMR results between the two solutes. Furthermore, most studies that were available and included in the meta-analysis were at significant risk of bias. There are also variations in the way sensitivity and specificity were measured. As shown in Table S4, due to the heterogenous nature of the L:M test, different cut-off point values were used in included studies for diagnosis of disease. There were also not many studies that assessed the value of the L:M test as a screening measure in coeliac or Crohn’s disease. Another limitation in this meta-analysis is in the variability in how active or inactive Crohn’s was defined as evidenced in Table S1. Crucially, however, most of these limitations are inherent to the L:M test itself. Thus, the fact that our results were heterogeneous highlights these important limitations to the L:M test and reveals that improvements are required if it is to be more widely used for clinical assessment of gut permeability. Overall, this review has quantified the diagnostic value of the L:M test and reported the LMR values in healthy subjects, treated and untreated coeliac disease, and inactive and active Crohn’s disease. In addition, it provides a quantification of the heterogeneity in LMR values observed in these disease states. Our analysis demonstrates that there is potential value in measuring gut permeability in both Crohn’s and coeliac disease, and it provides an insight into the role of gut permeability in the pathogenesis of both conditions. Importantly, however, it also highlights the limitations in the L:M test and the need for both improved protocols and alternative diagnostic tools. Conclusion Gut permeability is significantly impaired in untreated coeliac and Crohn’s disease. Gut barrier function is then recovered as patients are treated appropriately. These changes can be observed using the L:M test and this meta-analysis reports pooled LMR values in both diseases. While the L:M test can provide good diagnostic accuracy and offers some insight into gut permeability, it is limited by the lack of standardisation and the length of time required to conduct the test. Thus, if the L:M test is to find wider clinical use, then an optimised, standardised protocol needs to be determined and used. Even if this is achieved, the limited use of the L:M test may persist due to physiological variations between subjects and limitations in the accuracy of the test caused by changes in the permeation of mannitol. As such, there is a strong case for the development of new diagnostic tools that can provide faster, more accurate and more reliable quantification of gut permeability in a minimally or non-invasive manner. Such devices would have potential in monitoring progression/resolution of diseases such as coeliac and Crohn’s, and in identifying patients at risk of relapse. There is now an improved understanding of the increasing use of gut permeability analysis in patient care, and as a result, there is a concomitant need for robust evidence to develop this field for its next stage of healthcare innovation. Declarations Ethics approval and consent to participate: Not applicable Consent for publication: Not applicable Availability of data and materials: The dataset used and/or analysed during the current study are available from the corresponding author on reasonable request Competing interests: The authors declare that they have no competing interests Funding: National Institute for Health Research (NIHR) Imperial Biomedical Research Centre (BRC). Author contributions: JG: library search for literature review, data collation, analysis and co-authorship. SN: duplicate assessment of study bias and co-authorship. JT: staff supervisor and co-authorship. AD: staff supervisor and co-authorship. HA: staff supervisor, methodology expert and senior authorship. AT: staff supervisor, methodology expert and senior authorship. HA and AT contributed equally to this work. All authors read and approved the final manuscript. Acknowledgements: This article reports independent research funded by the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre (BRC). The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health. We would also like to acknowledge the contributions of Helen Elwell, the medical librarian, for her help in the literature identification process of the review. References Mayer EA, Tillisch K, Gupta A. Gut/brain axis and the microbiota. The Journal of clinical investigation. 2015 Mar 2;125(3):926-38. Camilleri M. Leaky gut: mechanisms, measurement and clinical implications in humans. Gut. 2019 Aug 1;68(8):1516-26. Canavan C, West J, Card T. The epidemiology of irritable bowel syndrome. Clinical epidemiology. 2014;6:71. Sequeira IR, Lentle RG, Kruger MC, Hurst RD. 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Smecuol E, Sugai E, Niveloni S, Vázquez H, Pedreira S, Mazure R, Moreno ML, Label M, Mauriño E, Fasano A, Meddings J. Permeability, zonulin production, and enteropathy in dermatitis herpetiformis. Clinical Gastroenterology and Hepatology. 2005 Apr 1;3(4):335-41. Gatti S, Caporelli N, Galeazzi T, Francavilla R, Barbato M, Roggero P, Malamisura B, Iacono G, Budelli A, Gesuita R, Catassi C. Oats in the diet of children with celiac disease: preliminary results of a double-blind, randomized, placebo-controlled multicenter Italian study. Nutrients. 2013 Nov;5(11):4653-64. Smecuol ED, Bai JC, Vazquez HO, Kogan ZU, Cabanne A, Niveloni SO, Pedreira SI, Boerr LU, Maurino ED, Meddings JB. Gastrointestinal permeability in celiac disease. Gastroenterology. 1997 Apr 1;112(4):1129-36. Smecuol E, Hwang HJ, Sugai E, Corso L, Chernavsky AC, Bellavite FP, González A, Vodánovich F, Moreno ML, Vázquez H, Lozano G. Exploratory, randomized, double-blind, placebo-controlled study on the effects of Bifidobacterium infantis natren life start strain super strain in active celiac disease. Journal of clinical gastroenterology. 2013 Feb 1;47(2):139-47. Hilsden RJ, Meddings JB, Hardin J, Gall GD, Sutherland LR. Intestinal permeability and postheparin plasma diamine oxidase activity in the prediction of Crohn's disease relapse. Inflammatory bowel diseases. 1999 May 1;5(2):85-91. Juby LD, Rothwell J, Axon AT. Lactulose/mannitol test: an ideal screen for celiac disease. Gastroenterology. 1989 Jan 1;96(1):79-85. Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors ). Cochrane Handbook for Systematic Reviews of Interventions version 6.1 (updated September 2020). Cochrane. 2020. Available from training.cochrane.org/handbook. Wan X, Wang W, Liu J, Tong T. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC medical research methodology. 2014 Dec 1;14(1):135. Musa MA, Mamun Kabir M, Hossain I, Ahmed E, Siddique A, Rashid H, Mahfuz M, Mondal D, Ahmed T, Petri WA, Haque R. Measurement of intestinal permeability using lactulose and mannitol with conventional five hours and shortened two hours urine collection by two different methods: HPAE-PAD and LC-MSMS. PloS one. 2019;14(8). Akram S, Mourani S, Ou CN, Rognerud C, Sadiq R, Goodgame RW. Assessment of intestinal permeability with a two-hour urine collection. Digestive diseases and sciences. 1998 Sep 1;43(9):1946-50. Sequeira IR, Lentle RG, Kruger MC, Hurst RD. Standardising the lactulose mannitol test of gut permeability to minimise error and promote comparability. PloS one. 2014;9(6). Lee GO, Kosek P, Lima AA, Singh R, Yori PP, Olortegui MP, Lamsam JL, Oliveira DB, Guerrant RL, Kosek M. Lactulose: mannitol diagnostic test by HPLC and LC-MSMS platforms: considerations for field studies of intestinal barrier function and environmental enteropathy. Journal of pediatric gastroenterology and nutrition. 2014 Oct;59(4):544. Matysiak-Budnik T, Candalh C, Dugave C, Namane A, Cellier C, Cerf-Bensussan N, Heyman M. Alterations of the intestinal transport and processing of gliadin peptides in celiac disease. Gastroenterology. 2003 Sep 1;125(3):696-707. Schulzke JD, Schulzke I, Fromm M, Riecken EO. Epithelial barrier and ion transport in coeliac sprue: electrical measurements on intestinal aspiration biopsy specimens. Gut. 1995 Dec 1;37(6):777-82. Bruewer M, Utech M, Ivanov AI, Hopkins AM, Parkos CA, Nusrat A. Interferon-γ induces internalization of epithelial tight junction proteins via a macropinocytosis-like process. The FASEB Journal. 2005 Jun;19(8):923-33. Drago S, El Asmar R, Di Pierro M, Grazia Clemente M, Sapone AT, Thakar M, Iacono G, Carroccio A, D'Agate C, Not T, Zampini L. Gliadin, zonulin and gut permeability: Effects on celiac and non-celiac intestinal mucosa and intestinal cell lines. Scandinavian journal of gastroenterology. 2006 Jan 1;41(4):408-19 Heyman M, Abed J, Lebreton C, Cerf-Bensussan N. Intestinal permeability in coeliac disease: insight into mechanisms and relevance to pathogenesis. Gut. 2012 Sep 1;61(9):1355-64. CUMMINS AG, THOMPSON FM, BUTLER RN, CASSIDY JC, GILLIS D, LORENZETTI M, SOUTHCOTT EK, WILSON PC. Improvement in intestinal permeability precedes morphometric recovery of the small intestine in coeliac disease. Clinical Science. 2001 Apr 1;100(4):379-86. Duerksen DR, Wilhelm-Boyles C, Veitch R, Kryszak D, Parry DM. A comparison of antibody testing, permeability testing, and zonulin levels with small-bowel biopsy in celiac disease patients on a gluten-free diet. Digestive diseases and sciences. 2010 Apr 1;55(4):1026-31. Xu P, Elamin E, Elizalde M, Bours PP, Pierik MJ, Masclee AA, Jonkers DM. Modulation of intestinal epithelial permeability by plasma from patients with Crohn’s Disease in a three-dimensional cell culture model. Scientific reports. 2019 Feb 14;9(1):1-1. Vivinus-Nebot M, Frin-Mathy G, Bzioueche H, Dainese R, Bernard G, Anty R, Filippi J, Saint-Paul MC, Tulic MK, Verhasselt V, Hebuterne X. Functional bowel symptoms in quiescent inflammatory bowel diseases: role of epithelial barrier disruption and low-grade inflammation. Gut. 2014 May 1;63(5):744-52. von Martels JZ, Bourgonje AR, Harmsen HJ, Faber KN, Dijkstra G. Assessing intestinal permeability in Crohn’s disease patients using orally administered 52Cr-EDTA. PloS one. 2019;14(2). Fasano A. All disease begins in the (leaky) gut: Role of zonulin-mediated gut permeability in the pathogenesis of some chronic inflammatory diseases. F1000Research. 2020;9. Thomson A, Smart K, Somerville MS, Lauder SN, Appanna G, Horwood J, Raj LS, Srivastava B, Durai D, Scurr MJ, Keita ÅV. The Ussing chamber system for measuring intestinal permeability in health and disease. BMC gastroenterology. 2019 Dec;19(1):98 Kosek M, Guerrant RL, Kang G, Bhutta Z, Yori PP, Gratz J, Gottlieb M, Lang D, Lee G, Haque R, Mason CJ. Assessment of environmental enteropathy in the MAL-ED cohort study: theoretical and analytic framework. Clinical Infectious Diseases. 2014 Nov 1;59(suppl_4):S239-47. Ordiz MI, Davitt C, Stephenson K, Agapova S, Divala O, Shaikh N, Manary MJ. EB 2017 Article: Interpretation of the lactulose: mannitol test in rural Malawian children at risk for perturbations in intestinal permeability. Experimental Biology and Medicine. 2018 May;243(8):677-83. Camilleri M, Nadeau A, Lamsam J, Linker Nord S, Ryks M, Burton D, Sweetser S, Zinsmeister AR, Singh R. Understanding measurements of intestinal permeability in healthy humans with urine lactulose and mannitol excretion. Neurogastroenterology & Motility. 2010 Jan;22(1):e15-26. Supplementary Files AdditionalFile126.1.21.docx Cite Share Download PDF Status: Published Journal Publication published 10 Jan, 2022 Read the published version in BMC Gastroenterology → Version 1 posted Editor assigned by journal 09 Feb, 2021 Submission checks completed at journal 09 Feb, 2021 Editor invited by journal 09 Feb, 2021 First submitted to journal 08 Feb, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-257838","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research article","associatedPublications":[],"authors":[{"id":12733631,"identity":"fa444c47-dc86-4b88-8ca9-160502f3ae15","order_by":0,"name":"Jonathan Gan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArUlEQVRIiWNgGAWjYBACxgYgkVAhAeUeIFrLGVK0QPS1wVjEaGHuX2P44OE8C3kG9sMPmHnOEGPBjDfGBonbJAwbeNIMmHluEKXl7DYJoJYEBoYcBmaeD8Rp2f4jcQ5QC/8bYrX0925jSGwAapEA2UKcw/g/SyQckzBsk3hmcHAOMd437D+W+PFHTZ08P3/ywwdvjhGjZUYChMHGQGxEyvMTp24UjIJRMApGMgAAKkQ0++Ct6tIAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-7410-1902","institution":"Imperial College London Department of Surgery and Cancer","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Jonathan","middleName":"","lastName":"Gan","suffix":""},{"id":12733632,"identity":"e85ca2a4-e2ba-4082-a9ac-e36f63802c08","order_by":1,"name":"Scarlet Nazarian","email":"","orcid":"","institution":"Imperial College London Department of Surgery and Cancer","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Scarlet","middleName":"","lastName":"Nazarian","suffix":""},{"id":12733633,"identity":"f57c5e80-c4b6-433c-9b3e-16ebeea80bb8","order_by":2,"name":"Julian Teare","email":"","orcid":"","institution":"Imperial College London Department of Surgery and Cancer","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Julian","middleName":"","lastName":"Teare","suffix":""},{"id":12733634,"identity":"101489c4-ef20-4aa4-8d2d-e41d96654cec","order_by":3,"name":"Ara Darzi","email":"","orcid":"","institution":"Imperial College London Department of Surgery and Cancer","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ara","middleName":"","lastName":"Darzi","suffix":""},{"id":12733635,"identity":"ac7c5093-4103-4d27-9ca8-48c96b46b7d4","order_by":4,"name":"Hutan Ashrafian","email":"","orcid":"","institution":"Imperial College London Department of Surgery and Cancer","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hutan","middleName":"","lastName":"Ashrafian","suffix":""},{"id":12733636,"identity":"7d26d82f-f4a5-4915-a293-e5c8e8da2c9c","order_by":5,"name":"Alex J. Thompson","email":"","orcid":"","institution":"Imperial College London Department of Surgery and Cancer","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Alex","middleName":"J.","lastName":"Thompson","suffix":""}],"badges":[],"createdAt":"2021-02-19 18:04:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-257838/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-257838/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12876-021-02082-z","type":"published","date":"2022-01-10T13:52:05+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":6369047,"identity":"0b71ecb7-8d41-479d-98cf-84dcfde79106","added_by":"auto","created_at":"2021-02-25 21:53:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":153903,"visible":true,"origin":"","legend":"Forest plot showing pooled LMR values (weighted mean) in healthy subjects.","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-257838/v1/59d64b6482f2bab90531f937.png"},{"id":6368874,"identity":"0b5d3b3f-c6f1-4831-974c-5779ecd6e699","added_by":"auto","created_at":"2021-02-25 21:50:52","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":763507,"visible":true,"origin":"","legend":"Forest plots showing pooled LMR (weighted mean) values in coeliac disease. (A) Untreated coeliac disease. (B). Treated coeliac disease.","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-257838/v1/cffdf3ad52d6e6a9942af9e2.jpeg"},{"id":6369048,"identity":"b8463e18-8dac-4379-9d4b-2b2832e12f96","added_by":"auto","created_at":"2021-02-25 21:53:52","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":176744,"visible":true,"origin":"","legend":"Forest plots showing pooled LMR values (weighted mean) in Crohn’s disease. (A) Inactive Crohn’s disease. (B) Active Crohn’s disease.","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-257838/v1/e75216951b432ed53fe3fdcd.png"},{"id":17159332,"identity":"5a3205d6-3b1c-4d79-b982-9f47c8ff8aff","added_by":"auto","created_at":"2022-01-10 13:52:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1076423,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-257838/v1/77ee9093-a903-4d50-a029-5e1675e794e2.pdf"},{"id":6368878,"identity":"4eccf6a1-c083-4d30-9a1f-0da7bf8bba9c","added_by":"auto","created_at":"2021-02-25 21:50:53","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":1128147,"visible":true,"origin":"","legend":"","description":"","filename":"AdditionalFile126.1.21.docx","url":"https://assets-eu.researchsquare.com/files/rs-257838/v1/ff11042b5be68e8bf1ba97a6.docx"}],"financialInterests":"","formattedTitle":"A case for improved assessment of gut permeability – a meta-analysis quantifying the lactulose:mannitol ratio in coeliac and Crohn’s disease","fulltext":[{"header":"Background","content":"\u003cp\u003eThere is emerging evidence that disturbances in gut barrier function play an important role in gastrointestinal (GI) diseases such as coeliac disease, inflammatory bowel disease (IBD), environmental enteric dysfunction, and in conditions outside the GI tract such as schizophrenia, autism and Parkinsons Disease\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Current established methods of measuring gut permeability in patients include the lactulose:mannitol (L:M) test, lactulose:rhamnose (L:R) test, chromium-51 labelled ethylenediamine tetraacetic acid (Cr-EDTA) assay, polyethylene glycol (PEG) test, use of Ussing chambers, analysis of haematological markers such as zonulin, and analysis of bacterial markers such as systemic lipopolysaccharide (LPS)\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Despite the various options available to measure gut permeability, their use in clinical settings is still limited\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFor the practising clinician, a reliable gut permeability assay could potentially provide a new way to monitor established diseases such as IBD and coeliac disease, and to develop a better understanding of functional gut disorders (FGDs). FGD is currently used as a \u0026lsquo;catch-all\u0026rsquo; term for poorly understood gastrointestinal conditions and treated as a diagnosis of exclusion. The impact of FGD on health systems is not to be underestimated. Globally, it affects 11% of the population and accounts for 20\u0026ndash;50% of gastroenterology outpatient work\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. A better appreciation of the link between gut permeability and FGD would aid the clinician in tackling this multi-faceted condition in a more effective manner.\u003c/p\u003e\u003cp\u003eOne of the widely used methods to measure small bowel permeability is the L:M test, in which, after a period of fasting, subjects are asked to drink a solute containing the two sugars lactulose and mannitol. Urinary excretion of both lactulose and mannitol are then measured several hours after ingestion of solute, and the lactulose:mannitol ratio (LMR) is calculated as an indicator of permeability\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe L:M test is useful as both sugars are passively absorbed from the intestine, not extensively metabolised, and excreted unchanged in urine in proportion to the quantities absorbed\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. The smaller sugar alcohol molecule (mannitol) is assumed to permeate transcellularly through the water pores of the membrane, whereas the larger disaccharide molecule (lactulose) is assumed to permeate paracellularly through the tight junctions\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. In states of increased gut permeability, lactulose would traverse through the paracellular spaces, cleared by glomerular filtration, not undergo selective reabsorption, and present itself in higher levels in urine, thus leading to an increased LMR.\u003c/p\u003e\u003cp\u003eThe L:M test is thought to be a good representative of gut permeability as measurements using a single molecule do not account for confounding factors such as intestinal transit time, gastric emptying rate, renal/hepatic function or total urinary excretion\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. By taking the ratio of excretion of two molecules, the effects of these confounding factors can be eliminated\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAlthough the L:M test has been in use since the 1970s\u003csup\u003e8\u003c/sup\u003e, it suffers from limitations, particularly in subjects where longitudinal urine collection is challenging (e.g. infants\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e and patients with reduced urinary output\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e). Furthermore, absolute LMR values for the small bowel in healthy subjects and in disease are not yet established. To address this issue, we performed a meta-analysis to quantify LMR values in healthy participants and in various states of coeliac and Crohn\u0026rsquo;s disease, two conditions in which altered gut permeability is observed. The results of this meta-analysis are presented below, and variations in the methods used to conduct the L:M test are also explored. To the best of our knowledge, there are not many meta-analyses presented on the L:M test in coeliac and Crohn\u0026rsquo;s disease. The results highlight the limitations of the test and the improvements required to bring measurements of gut permeability into larger scale clinical use.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eA systematic review was conducted according to the recommendations in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Prior to conducting the meta-analysis, the eligibility criteria, description of intervention, and comparison and outcome of interest were established. The literature search was conducted by two independent reviewers.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eEligibility criteria\u003c/h2\u003e\u003cp\u003eWe included all observational studies, cross-sectional studies, cohort studies and trials pertaining coeliac and Crohn\u0026rsquo;s disease. We excluded papers that did not report absolute LMR values as well as in vitro studies, animal studies, and studies where sample groups were mixed (e.g. Crohn\u0026rsquo;s plus ulcerative colitis). Studies had to be published in peer reviewed journals and the search was not restricted by language.\u003c/p\u003e\u003cp\u003e\u003cem\u003eLiterature identification\u003c/em\u003e\u003c/p\u003e\u003cp\u003eIn January 2020, with the help of a medical librarian, literature searches were conducted using the following databases: Embase (1988\u0026ndash;2020); Ovid MEDLINE In Process \u0026amp; Other Non-Indexed Citations and Ovid MEDLINE (1946 to Present); and Cochrane Database of Systematic Reviews. Terms and/or abbreviations to describe coeliac, Crohn\u0026rsquo;s disease and gut permeability were combined into a search strategy textbox. Free-text terms were then used in various combinations to ensure a complete search in the databases mentioned above. The combined searches relating to gut permeability in coeliac and Crohn\u0026rsquo;s disease were explored using the terms \u0026lsquo;and\u0026rsquo; and 'or\u0026rsquo;. The following search terms were used: \u0026lsquo;\u0026lsquo;permeability\u0026rsquo;\u0026rsquo;, \u0026lsquo;\u0026lsquo;leaky or leakiness\u0026rsquo;\u0026rsquo;, \u0026lsquo;\u0026lsquo;lactulose mannitol\u0026rsquo;\u0026rsquo;, \u0026lsquo;\u0026lsquo;inflammatory bowel disease or IBD\u0026rsquo;\u0026rsquo;, \u0026lsquo;Crohn\u0026rsquo;s Disease\u0026rsquo;, \u0026lsquo;coeliac disease\u0026rsquo;, \u0026lsquo;Crohn\u0026rsquo;s\u0026rsquo;\u0026rsquo;, and \u0026lsquo;\u0026lsquo;coeliac\u0026rsquo;\u0026rsquo;.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003eStudy selection\u003c/h2\u003e\u003cp\u003eThe titles and abstracts of the search were then screened. Full text articles or abstracts of potentially relevant references in the articles also underwent review. Conference abstracts and papers with no full texts available were excluded. The study selection process was performed by two independent reviewers who were blinded (JG and SN), and any disagreements were resolved by a third author (HA). JG and SN appraised quality independently.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eData extraction\u003c/h2\u003e\u003cp\u003eThe following information was extracted from the studies chosen by JG and SN: number of patients, study objectives, study methodology, results, type of population, L:M study protocol, type of solute given to subjects, urine collection time, method of urine analysis and LMR values. Data extracted were then tabulated in Microsoft Excel and the study outcomes were reviewed by a third reviewer (AT).\u003c/p\u003e\u003cp\u003eThe primary study outcomes were Standardised Mean Differences (SMD) of LMR values in healthy controls, treated coeliac patients, untreated coeliac patients, patients with active Crohn\u0026rsquo;s disease, and patients with inactive Crohn\u0026rsquo;s disease. The secondary outcomes were comparisons of use of different concentrations of lactulose and mannitol (5 parts lactulose to 2 parts mannitol, and 2 parts lactulose to 1 part mannitol) in the aforementioned groups.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eRisk of bias assessment\u003c/h2\u003e\u003cp\u003eRandomised control trials (RCTs) were assessed using the Jadad score\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, while non-randomised trials were assessed using the Risk Of Bias In Non-randomised Studies of Interventions tool (ROBINS-I)\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. The Newcastle Ottawa Score (NOS) was used for cohort and case control studies\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. The risk of bias in all studies was assessed by two independent reviewers. The parameters assessed in cohort and case control studies included study design, outcome measurements, representativeness of cases, control selections, ascertainment of exposure, and follow up rate. Using the ROBINS-I assessment tool, potential bias was assessed pre-intervention, at intervention and post intervention. For studies assessed using the NOS or the Jadad score, a single bias value was calculated for each study.\u003c/p\u003e\u003cp\u003eIn the NOS assessment, a score of \u0026le;\u0026thinsp;3 indicates poor quality, 4\u0026ndash;6 moderate quality, and \u0026ge;\u0026thinsp;7 good quality. Under the Jadad scoring system, good studies will score\u0026thinsp;\u0026ge;\u0026thinsp;3, and poor studies will score\u0026thinsp;\u0026lt;\u0026thinsp;3. The ROBINS-I tool ranks the risk of bias in studies as \u0026lsquo;low risk\u0026rsquo;, \u0026lsquo;moderate risk\u0026rsquo;,\u0026rsquo;serious risk\u0026rsquo;, \u0026lsquo;critical risk\u0026rsquo; or \u0026lsquo;no information\u0026rsquo;. The findings from the two assessors were evaluated by a third reviewer.\u003c/p\u003e\u003cp\u003eRisk of bias was also assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. The tool consists of four domains: patient selection, index test, reference standard, and flow of timing. Each domain is assessed in terms of risk of bias. The first three domains are also assessed in terms of applicability to clinical practice.\u003c/p\u003e\u003cp\u003eAll three modes of assessment were performed by J.G and S.N, and any disagreements were resolved by consensus and discussion with the other authors.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eStata 15 (StataCorp, College Station, Texas) was used for the statistical analysis reported in this study. All analyses were performed using a random effects model in response to expected heterogeneity of data collected. In order to calculate weighted mean and standard mean values of LMR, values of LMR reported in individual studies were pooled into healthy controls, patients with untreated coeliac disease, patients with treated coeliac disease, patients with active Crohn\u0026rsquo;s and patients with inactive Crohn\u0026rsquo;s disease. The definition of active Crohn\u0026rsquo;s and inactive Crohn\u0026rsquo;s in individual papers are listed in Table S1.\u003c/p\u003e\u003cp\u003eThe Weighted Mean Difference (WMD) and Standard Mean Difference (SMD) of LMR were calculated between controls and treated coeliac, controls and untreated coeliac, treated and untreated coeliac, controls and inactive Crohn\u0026rsquo;s disease, controls and active Crohn\u0026rsquo;s disease, and active and inactive Crohn\u0026rsquo;s disease. This approach calculated overall weighted mean and standard mean differences (i.e. incorporating all relevant studies included in this meta-analysis) and also ascribed an individual weighted mean and standard mean difference for each individual study with 95% Confidence Intervals (CIs). The weighted mean differences refer to the pooled estimates, with the 'weighted' component referring to the different weights applied to each study (or each patient/participant group) in the overall calculation. This was done to accommodate the different sizes (participant number) of studies included in this meta-analysis and the different sizes of patient/participant groups within studies. Weighted mean differences and weighted mean values were calculated in line with principles set out by Egger et al\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eMeta-analysis of summary estimates of proportions was also calculated for overall LMRs and sensitivities and specificities. All results for pooled estimates were presented with 95% CIs. I\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e values were calculated to assess heterogeneity. P values were calculated using the chi-squared test, and the results were considered significant for P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. We note that for studies in which paired data were reported (i.e. where LM ratios were measured before and after treatment), pre- and post-treatment LMR values were simply allocated into the appropriate groups (i.e. paired data was not treated differently to unpaired data).\u003c/p\u003e\u003cp\u003eA bivariate model for diagnostic meta-analysis was used to compute pooled sensitivity and specificity data where available. The relationship between sensitivity and specificity was assessed using a hierarchical summary receiver operating characteristic (SROC) model. SROC curves were utilized to convey the diagnostic test performance and a prediction region curve was also plotted. Trapezoidal integration was used to calculate the pooled area under the curve (AUC), where 0.5 implies that a test was equally likely to diagnose a positive result as either positive or negative and a value of 1.0 indicates a \u0026lsquo;perfect\u0026rsquo; test that gives a 100% correct diagnosis. A pooled AUC value of 0.75 or above represents a test with good accuracy\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. The \u0026lsquo;gold standard\u0026rsquo; test that we used for the sensitivity and specificity assessment was intestinal biopsy.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eSearch results and study description\u003c/h2\u003e\u003cp\u003eAfter performing general searches for the relevant subjects and combining them, 377 abstracts were extracted from Medline, 569 abstracts were found in Embase and 190 in the Cochrane. After duplicates were removed, we found that the total number of relevant abstracts was 633.\u003c/p\u003e\u003cp\u003e50 abstracts were found to be relevant to coeliac disease. Of these, a further 31 studies were excluded as per the exclusion criteria discussed above, meaning that a total of 19 coeliac disease studies were selected for analysis. We found that 97 studies were relevant to Crohn\u0026rsquo;s disease. Of these, 80 studies were excluded according to the exclusion criteria discussed above. Hence, a total of 17 Crohn\u0026rsquo;s disease studies were included in this meta-analysis. These results are summarised in the PRISMA flow diagrams (Fig S1 and S2).\u003c/p\u003e\u003cp\u003eThe selected studies pertaining gut permeability in Crohn\u0026rsquo;s disease and coeliac disease are tabulated in Tables S1 and S2 respectively\u003csup\u003e\u003cspan additionalcitationids=\"CR19 CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29 CR30 CR31 CR32 CR33 CR34 CR35 CR36 CR37 CR38 CR39 CR40 CR41 CR42 CR43 CR44 CR45 CR46 CR47 CR48 CR49 CR50\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e. Altogether, there were 15 studies that investigated gut permeability in Crohn's disease specifically using the L:M test, 17 studies that investigated gut permeability in coeliac disease specifically using the L:M test, and 2 studies that investigated both Crohn\u0026rsquo;s and coeliac using the L:M test.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eMeta-analysis of results\u003c/h2\u003e\u003cp\u003eThe median LMR values, and weighted and standard mean difference values calculated for each study are presented in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. In studies where the median LMR value was unavailable, the mean value was used. Standard deviation values associated with each LMR presented in Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e were either as stated in the individual studies, or if unavailable, were derived from the published range, interquartile range (IQR), 95% CI or standard error of mean (SEM) using established statistical methods\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\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\u003eSummary of number (no) of patients/participants and lactulose:mannitol ratios (LMRs) reported in untreated coeliac patients, treated coeliac patients, and healthy controls. Where appropriate data was available, the calculated weighted mean difference (WMD) and standard mean difference (SMD) in LMR (between the coeliac cohort and healthy controls) are also shown. *=mean value, **=unknown if value is mean or median, \u0026#133;=Standard deviation (SD) calculated from range, \u0026#133;\u0026#133;=SD calculated from interquartile range (IQR), \u0026#133;\u0026#133;\u0026#133;=SD calculated from standard error of mean (SEM), \u0026#133;\u0026#133;\u0026#133;\u0026#133;=SD calculated from 95% confidence interval (CI).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"13\"\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStudy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo of healthy controls\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReported LMR in healthy controls\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eStandard Deviation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNo of untreated coeliac patients\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eReported LMR in untreated coeliac\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eStandard Deviation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eNo of treated coeliac patients\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eReported LMR in treated coeliac patients\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eStandard Deviation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eStatistically calculated WMD (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003eStatistically calculated SMD (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\u003eElia et al 1991\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.021*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.020\u003csup\u003e\u0026#133;\u0026#133;\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.152*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.120\u003csup\u003e\u0026#133;\u0026#133;\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.131 (0.070, 0.192)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e1.736 (0.979, 2.492)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVogelsang et al 2001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTreated vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.058\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.028\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.092 (0.061, 0.123)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e2.085 (1.252, 2.919)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKuitunen et al 1996\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.030\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.043\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.260\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.410\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.230 (0.058, 0.402)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.751 (0.106, 1.397)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKuitunen et al 1996\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs treated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.030\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.043\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.040\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.010\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.010 (-0.010, 0.030)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.316 (-0.351, 0.983)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKuitunen et al 1996\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTreated vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.260\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.410\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.040\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.010\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.220 (0.049, 0.391)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.712 (0.059, 1.365)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUkabam et al 1985\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.003\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.156\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.101 (0.016, 0.186)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e1.121 (0.402, 1.839)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUkabam et al 1985\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs treated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.003\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.016\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.007 (-0.002, 0.016)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.728 (0.037, 1.419)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUkabam et al 1985\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTreated vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.156\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.016\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.094 (0.009, 0.179)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.848 (0.042, 1.653)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVilela et al 2008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs treated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.003\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.016\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.010 (0.003, 0.017)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.785 (0.103, 1.466)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHamilton et al 1987\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.021\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.296*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.308\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.264 (-1.018, 1.546)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.688 (-0.362, 1.739)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarsilio et al 1998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.024*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.072*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.048 (0.032, 0.064)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e3.623 (2.539, 4.708)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVan Elburg et al 1993\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.043*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.030\u003csup\u003e\u0026#133;\u0026#133;\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.243*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.100\u003csup\u003e\u0026#133;\u0026#133;\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.200 (0.133, 0.267)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e3.425 (2.251, 4.599)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRajani et al 2016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.016\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.070\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.021 (0.003, 0.039)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.351 (-0.106, 0.809)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRajani et al 2016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs treated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.016\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.077\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.002 (-0.021, 0.025)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.032 (-0.447, 0.511)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRajani et al 2016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTreated vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.070\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.077\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.019 (0.009, 0.047)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.261 (0.155\u0026ndash;0.638)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmecuol et al 1997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTreated vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.360*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.380\u003csup\u003e\u0026#133;\u0026#133;\u0026#133;\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.130*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.188\u003csup\u003e\u0026#133;\u0026#133;\u0026#133;\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.230 (0.058, 0.402)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.706 (0.056, 1.356)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmecuol et al 2005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.017*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.040\u003csup\u003e\u0026#133;\u0026#133;\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.073*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.090\u003csup\u003e\u0026#133;\u0026#133;\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.056 (0.021, 0.091)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.804 (0.277, 1.331)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJuby et al 1989\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.016*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.007\u003csup\u003e\u0026#133;\u0026#133;\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.163*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.313\u003csup\u003e\u0026#133;\u0026#133;\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.147 (-0.002, 0.296)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.610 (-0.147, 1.367)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNovacek et al 1999a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUntreated coeliac disease with normal liver function tests\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e106\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.315\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNovacek et al 1999b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUntreated coeliac disease with abnormal liver function tests before vs after gluten free diet\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.340\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.400\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.070\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.290 (0.034, 0.614)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.284 (0.054, 0.623)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVecsei et al 2009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTreated vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.177\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.053\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJohnston et al 2000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.013*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.105*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJohnston et al 2000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs treated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.013*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.013*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJohnston et al 2000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTreated vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.105*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.013*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCatassi et al 1997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs untreated coeliac\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.038\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmecuol et al 1999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUntreated coeliac disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.101\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.069\u003csup\u003e\u0026#133;\u0026#133;\u0026#133;\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmecuol et al 2013a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUntreated coeliac disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.159\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmecuol et al 2013b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUntreated coeliac disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.054\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.440\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGatti et al 2013a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTreated coeliac disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.04\u003csup\u003e\u0026#133;\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGatti et al 2013b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTreated coeliac disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.055\u003csup\u003e\u0026#133;\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\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 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSummary of number (no) of patients/participants and lactulose:mannitol ratios (LMRs) reported in patients with active Crohn\u0026rsquo;s disease, patients with inactive Crohn\u0026rsquo;s disease, and healthy controls. Where appropriate data was available, the calculated weighted mean difference (WMD) and standard mean difference (SMD) in LMR (between the Crohn\u0026rsquo;s cohort and healthy controls) are also shown. *=mean value, **=unknown if value is mean or median, \u0026#133;=Standard deviation (SD) calculated from range, \u0026#133;\u0026#133;=SD calculated from interquartile range (IQR), \u0026#133;\u0026#133;\u0026#133;=SD calculated from standard error of mean (SEM), \u0026#133;\u0026#133;\u0026#133;\u0026#133;=SD calculated from 95% confidence interval (CI).\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"13\"\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStudy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNumber of healthy controls\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReported LMR in healthy controls\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eStandard deviation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNumber of active Crohn\u0026rsquo;s patients\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eReported LMR in active Crohn's\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eStandard deviation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eNumber of inactive Crohn\u0026rsquo;s patients\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eReported LMR in inactive Crohn's\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c11\"\u003e\u003cp\u003eStandard deviation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c12\"\u003e\u003cp\u003eStatistically calculated WMD (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c13\"\u003e\u003cp\u003eStatistically calculated SMD (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\u003eMarsilio et al 1998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs active Crohn\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.024*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.200*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.082\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.176 (0.125, 0.227)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e4.373 (3.157, 5.589)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVilela et al 2008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs inactive Crohn\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.003\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.006\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.018 (0.015, 0.021)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e3.467 (2.516, 4.418)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDastych et al 2008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs active Crohn\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.012*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.076*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.064 (0.047, 0.081)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e2.396 (1.575, 3.217)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD'Inca et al 2006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs inactive Crohn\u0026rsquo;s vs first degree relatives\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.003\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.045\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.020 (0.012, 0.028)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.506 (0.123, 0.889)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWild et al 2003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs inactive Crohn\u0026rsquo;s patients after 10 weeks of tapering steroids who eventually relapsed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.021*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.055*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.05 (0.04, 0.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e3.209 (2.144, 4.274)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWild et al 2003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs inactive Crohn\u0026rsquo;s patients after 10 weeks of tapering steroids who eventually did not relapse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.021*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.026*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.497 (-0.232, 1.225)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWild et al 2003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs active Crohn\u0026rsquo;s patients\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.021*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.088*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.067 (0.058, 0.076)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e3.387 (2.534, 4.240)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWild et al 2003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eActive Crohn\u0026rsquo;s patients vs inactive Crohn\u0026rsquo;s patients after 10 weeks of tapering steroids who eventually relapsed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.088*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.055*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.033 (0.019, 0.047)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e1.364 (0.609, 2.118)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWild et al 2003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eActive Crohn\u0026rsquo;s patients vs inactive Crohn\u0026rsquo;s patients after 10 weeks of tapering steroids who eventually did not relapse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.088*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.026*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.062 (0.048, 0.076)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e2.582 (1.684, 3.479)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGarcia Vilela et al 2008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs inactive Crohn\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.005*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.021*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.016 (0.012, 0.020)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e1.879 (1.148, 2.609)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSigalet et al 2013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs active Crohn\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.029*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.056*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.026 (0.007, 0.045)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e1.531 (0.421, 2.641)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSigalet et al 2013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs inactive Crohn\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.029*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.032*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.002 (-0.007, 0.011)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.226 (-0.743, 1.195)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSigalet et al 2013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eActive vs inactive Crohn\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.056*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.032*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.024 (0.004, 0.044)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e1.261 (0.098, 2.423)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZamora et al 1999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs inactive Crohn\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.01\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.040\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.008 (-0.013,0.030)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.313 (-0.368, 0.993)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAndre et al 1988\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs active Crohn\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.021*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.132*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.111 (0.055, 0.167)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e2.787 (2.134, 3.440)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAndre et al 1988\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs inactive Crohn\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.021*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.074*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.090\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.053 (0.007,0.099)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e1.604 (1.023, 2.186)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAndre et al 1988\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eActive vs inactive Crohn\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.132*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.074*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.090\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.058 (-0.014, 0.130)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.577 (-0.154, 1.309)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSturniolo et al 2001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInactive Crohn\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.041*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBuhner et al 2006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs inactive Crohn\u0026rsquo;s vs first degree relatives vs non-blood relatives\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.005\u003csup\u003e\u0026#133;\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.016\u003csup\u003e\u0026#133;\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.011 (0.008, 0.014)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.877 (0.601, 1.154)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD'Inca et al 1999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs Inactive Crohn\u0026rsquo;s patients who eventually relapsed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.009*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.045*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.036 (0.025, 0.047)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e1.359 (0.973, 1.745)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD'Inca et al 1999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs Inactive Crohn\u0026rsquo;s patients who eventually did not relapse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.009*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.027*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e\u003cp\u003e0.018 (0.012, 0.024)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e\u003cp\u003e0.938 (0.610, 1.267)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSwanson et al 2011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControl vs inactive Crohn\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.094\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.085\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBenjamin et al 2012a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInactive Crohn\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.067\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.024\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBenjamin et al 2012b\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInactive Crohn\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.071\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.061\u003csup\u003e\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHilsden et al 1996\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControls vs first degree relatives of Crohn\u0026rsquo;s patients in remission\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.017*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.006\u003csup\u003e\u0026#133;\u0026#133;\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHilsden et al 1999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInactive Crohn\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e\u003cp\u003e0.018*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBreslin et al 2001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eControls vs spouses of patients with inactive Crohn\u0026rsquo;s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.017*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.005\u003csup\u003e\u0026#133;\u0026#133;\u0026#133;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ePooled analysis of gut permeability results in healthy subjects analysed in 24 studies (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) revealed a LMR value of 0.014 (95% CI: 0.006 to 0.022). In untreated and treated coeliac patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA \u0026amp; \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB), the pooled LMR values were 0.133 (95% CI: 0.089 to 0.178) and 0.037 (95% CI: 0.019 to 0.055) respectively. In inactive Crohn\u0026rsquo;s disease (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), the pooled LMR 0.028 (95% CI: 0.015 to 0.041), while in active Crohn\u0026rsquo;s disease (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), the pooled LMR was 0.093 (95% CI: 0.031 to 0.156).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003eLMR comparisons in coeliac disease\u003c/h2\u003e\u003cp\u003eThe SMD and WMD in LMR between healthy controls and treated coeliac disease (4 studies) was 0.409 (95% CI: 0.034 to 0.783, p\u0026thinsp;=\u0026thinsp;0.032, Fig S3A) and 0.009 (95% CI 0.003 to 0.014, p\u0026thinsp;=\u0026thinsp;0.001, Fig S3B) respectively. The SMD and WMD in LMR between healthy controls and patients with untreated coeliac disease (9 studies) were calculated as 1.362 (95% CI: 0.740 to 1.984, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig S3C) and 0.090 (95% CI: 0.054 to 0.126, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig S3D) respectively. The results exhibited high heterogeneity for comparison between healthy controls and untreated coeliac (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;84.8%), but this was not the case not for the comparison between healthy controls and treated coeliac (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;31.7%). The SMD and WMD in LMR between treated and untreated coeliac disease (6 studies) were 0.722 (95% CI: 0.286 to 1.157, p\u0026thinsp;=\u0026thinsp;0.001, Fig S3E) and 0.101 (95% CI: 0.040 to 0.162, p\u0026thinsp;=\u0026thinsp;0.001, Fig S3F) respectively, and the results were found to be heterogenous (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;72.9%).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003eLMR comparisons in Crohn\u0026rsquo;s disease\u003c/h2\u003e\u003cp\u003e11 studies were included in comparisons of LMR values in Crohn\u0026rsquo;s disease. 9 studies were included in the pooled random effects analysis of LMR in healthy controls vs. inactive Crohn\u0026rsquo;s disease, revealing a SMD and WMD of 1.265 (95% CI: 0.845 to 1.686, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig S4A) and 0.017 (95% CI: 0.012 to 0.022, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig S4B) respectively. 5 studies comparing healthy controls and active Crohn\u0026rsquo;s disease were identified, showing a SMD and WMD in LMR of 2.868 (95% CI: 2.112 to 3.623, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig S4C) and 0.078 (95% CI: 0.049 to 0.107, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig S4D) respectively. High heterogeneity was observed in both comparisons (I\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e values of 85.8% and 71.8% respectively). 3 studies were included in the comparison of active and inactive Crohn\u0026rsquo;s disease, showing a SMD and WMD of 1.429 (95% CI: 0.580 to 2.278, p\u0026thinsp;=\u0026thinsp;0.001, Fig S4E) and 0.042 (95% CI: 0.021 to 0.063, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig S4F) respectively, and the results were found to be heterogenous (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;74%).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eSubgroup comparisons using different solutes\u003c/h2\u003e\u003cp\u003eWe also sought to examine if there were any differences in the results obtained when using different lactulose:mannitol ratios in the solutes given to patients during the L:M test. The solutes used in the studies cited here can be broadly divided into ratios of 5:2 (5 parts lactulose to 2 parts mannitol) and 2:1 (2 parts lactulose to 1 part mannitol).\u003c/p\u003e\u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\u003ch2\u003e5:2 solute used in Crohn\u0026rsquo;s and coeliac disease\u003c/h2\u003e\u003cp\u003eUsing 5:2 solutes, the SMD and WMD in LMR between healthy controls and untreated coeliac disease (6 studies) were found to be 1.495 (95% CI: 0.549 to 2.441, p\u0026thinsp;=\u0026thinsp;0.002) and 0.072 (95% CI: 0.033 to 0.11, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) respectively. This was associated with high heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;89.6%). In treated vs untreated coeliac disease (2 studies), the SMD and WMD in LMR were 0.401 (95% CI: -0.003 to 0.806, p\u0026thinsp;=\u0026thinsp;0.052) and 0.107 (95% CI: -0.097 to 0.311, p\u0026thinsp;=\u0026thinsp;0.305) respectively. This was associated with low heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;25.6%). Only one study was found in which healthy controls were compared with treated coeliac patients using 5:2 solutes and hence no analysis was done for this.\u003c/p\u003e\u003cp\u003eIn studies comparing patients with Crohn\u0026rsquo;s disease and healthy subjects, 4 studies were found using 5:2 solutes. The SMD and WMD in LMR between inactive Crohn\u0026rsquo;s disease and healthy controls (2 studies) were 0.284 (95% CI: -0.273 to 0.841, p\u0026thinsp;=\u0026thinsp;0.318) and 0.003 (95% CI: -0.005 to 0.011, p\u0026thinsp;=\u0026thinsp;0.486) respectively. The heterogeneity of results was low (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0%). The analysis of SMD and WMD in LMR between active Crohn\u0026rsquo;s disease and healthy controls (2 studies) revealed a difference 2.941 (95% CI: 0.156 to 5.725, p\u0026thinsp;=\u0026thinsp;0.038) and 0.099 (95% CI: -0.048 to 0.246, p\u0026thinsp;=\u0026thinsp;0.186) respectively, and the results were highly heterogeneous (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;91.3%). Only 1 study was found where inactive vs active Crohn\u0026rsquo;s was compared using the 5:2 solute and hence no analysis was done for this.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\u003ch2\u003e2:1 solute used in Crohn\u0026rsquo;s and coeliac disease\u003c/h2\u003e\u003cp\u003e9 studies investigated the difference in LMR between healthy controls and coeliac disease using the 2:1 solute. Comparing healthy controls against untreated coeliac disease (4 studies), the SMD and WMD in LMR were calculated as 1.737 (95% CI: 0.701 to 2.773, p\u0026thinsp;=\u0026thinsp;0.001) and 0.103 (95% CI: 0.038 to 0.167, p\u0026thinsp;=\u0026thinsp;0.002) respectively. This was associated with high heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;85.9%). Comparing LMR in healthy controls against treated coeliac disease in 3 studies revealed a SMD and WMD of 0.604 (95% CI: 0.212 to 0.997, p\u0026thinsp;=\u0026thinsp;0.003) and 0.009 (95% CI: 0.004\u0026ndash;0.014, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) respectively, which was associated with low heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0%). Analysis of SMD and WMD in LMR between treated and untreated coeliac patients (4 studies) revealed a difference of 0.992 (95% CI: 0.200 to 1.645, p\u0026thinsp;=\u0026thinsp;0.012) and 0.103 (95% CI 0.061 to 0.144, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) respectively, and this was associated with high heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;81.3%).\u003c/p\u003e\u003cp\u003e9 studies performed comparisons of LMR in patients with Crohn\u0026rsquo;s disease using the 2:1 solute. Analysis of 6 studies comparing SMD and WMD in healthy controls and inactive Crohn\u0026rsquo;s disease revealed a change of 1.442 (95% CI: 0.944 to 1.941, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and 0.018 (95% CI: 0.014\u0026ndash;0.023, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) respectively which was associated with high heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;88.3%). 3 studies were found comparing healthy controls and active Crohn\u0026rsquo;s disease, and analysis revealed SMD and WMD in LMR of 3.312 (95% CI: 2.257 to 4.366, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and 0.089 (95% CI: 0.056 to 0.121, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) with high heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;73%). Only 1 study was found where inactive vs active Crohn\u0026rsquo;s was compared using the 2:1 solute and hence no analysis was done for this.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eSensitivity and specificity analysis\u003c/h2\u003e\u003cp\u003e We analysed the sensitivity and specificity based on the available data in the papers included in our review. 4 studies reported diagnostic accuracies for the L:M test in screening for coeliac disease. The sensitivity and specificity data are presented in Table S4. Pooled specificity (Fig S5A) was calculated as 0.700 (95% CI: 0.551\u0026ndash;0.849), and pooled sensitivity (Fig S5B) was calculated as 0.829 (95% CI: 0.682\u0026ndash;0.976). However, the overall heterogeneity for sensitivity and specificity was high (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;94.3% and 78.4% respectively).\u003c/p\u003e\u003cp\u003eSensitivity and specificity values for coeliac disease were also calculated based on a SROC curve (Fig S5C). The pooled, weighted AUC was calculated as 0.88 (95% CI: 0.85\u0026ndash;0.91). Based on the SROC graph, the estimated positive likelihood ratio was 4.0 (95% CI: 1.5\u0026ndash;10.6) and the estimated negative likelihood ratio was 0.15 (95% CI: 0.04\u0026ndash;0.6). The estimated diagnostic odds ratio was 27 (95% CI: 4-194). The estimated sensitivity and specificity from the SROC graph were 0.89 (95% CI: 0.62\u0026ndash;0.97) and 0.78 (95% CI: 0.51\u0026ndash;0.92) respectively, in agreement with the pooled results reported above.\u003c/p\u003e\u003cp\u003eSensitivity and specificity analysis were not performed for Crohn\u0026rsquo;s disease due to paucity of data in the studies included in our meta-analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eRisk of bias assessment\u003c/h2\u003e\u003cp\u003eIn 30 studies where the Newcastle Ottawa Score was used to assess bias, 9 studies had low risk, 20 had moderate risk, and 1 had high risk of bias. Risk of bias was assessed using the Jadad score in 4 RCT studies, and we found that 3 studies were of good quality, and 1 study was of poor quality. 5 studies were assessed using the ROBINS-I tool, and we found that 2 studies had moderate risk of bias and 3 studies had serious risk of bias. Assessment using the QUADAS-2 tool raised several methodologic limitations, such as the absence of an index test due to the heterogeneity associated with the conduct of the lactulose mannitol test (hence there are concerns about the applicability of the index test), and the difficulty in assessing if the reference standard set in each study was interpreted without the knowledge of the results of any index test performed (hence the risk of bias in the reference standard domain is \u0026lsquo;unknown\u0026rsquo;). The detailed assessments of bias in each domain using the Jadad score, NOS, ROBINS-1 tool and QUADAS-2 tool are described in the Supplementary material (Tables B1-B7).\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOverall, this meta-analysis demonstrates that despite considerable heterogeneity in the data, there are significant differences in LMR between healthy subjects and patients with either coeliac or Crohn\u0026rsquo;s disease. There are also significant differences in LMR between treated and untreated coeliac, and active compared to inactive Crohn\u0026rsquo;s disease.\u003c/p\u003e\u003cp\u003eThese results hold true even when different L:M solute ratios are used. Altogether, there were 18 studies that used a 2:1 ratio of lactulose to mannitol, and 13 studies that used a 5:2 ratio. While no previous studies have performed direct comparisons of the data obtained using different solute ratios, we found that standard mean differences in LMR were larger when using the 2:1 ratio than the 5:2 (although high heterogeneity in the data means that this observation should be taken with caution, and statistical significance was not observed). However, the numbers in each subgroup were small, which may explain the mixed significances and heterogeneities observed. Nevertheless, this raises the possibility that the heterogenous nature of our results could be attributed to the different L:M solute ratios used, along with other factors such as assay method, time of fasting before the solute is administered, and urine collection times.\u003c/p\u003e\u003cp\u003eMusa et al. found no significant difference in LMR when comparing prolonged urine collection time (5 hours) with urine collected over a 2 hour period\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. In the same study, they also found no significant differences when using two different analysis methods: high-performance anion exchange chromatography with derivatization-free, pulsed amperometric detection (HPAE-PAD); and liquid chromatography with tandem mass spectrometry (LC-MSMS)\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. This concurred with results from Akram\u0026rsquo;s earlier study regarding urine collection, which found no significant differences in LMR when urine was collected over 2 and 6 hours\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. Camilleri et al., on the other hand, found that LMR based on urine collections over 8\u0026ndash;24 hours were significantly higher than those for collections times of 0\u0026ndash;2 hours\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Interestingly, a study by Sequeira and colleagues suggested that differences in temporal patterns of excretion of lactulose and mannitol can be minimised if the urine collection period is restricted to 2\u0026frac12;4 hours after solute ingestion\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn relation to analysis platforms used for quantification of urinary lactulose and mannitol, Lee et al. found that LC-MSMS provides more accurate measurements than HPAE-PAD\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. They subsequently recommended the former to be used in L:M studies. Nonetheless, current evidence surrounding the variable protocols used in L:M studies (e.g. in terms of the analysis platforms, solute ratios and urinary collection times used) is mixed, and more studies are required to elucidate the optimal method for performing this test.\u003c/p\u003e\u003cp\u003eDespite the variability and heterogeneity observed, we found significant differences in LMR between healthy controls and untreated coeliac disease. Patients with active coeliac disease are known to have flat mucosa, increased villous height, and increased paracellular permeability due to wider tissue junction pores and release of pro-inflammatory cytokines\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. Gluten is thought to activate zonulin signalling, which opens up the tight junctions, causing increased paracellular permeability\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. The role of gut permeability in the pathogenesis of coeliac disease is currently poorly understood, but it is thought that it might act to self-sustain the inflammatory response and perpetuate a vicious cycle\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. Regardless, the increased permeability leads to an increase in lactulose excretion into urine, resulting in significantly higher LMR values than those observed in healthy subjects.\u003c/p\u003e\u003cp\u003eDifferences in LMR between treated and untreated coeliac disease were also observed and found to be significant, with the change in LMR observed across all coeliac studies included in this review. These changes need to be analysed with caution, however, as the results were heterogenous and the 95% confidence interval was fairly wide (0.029\u0026ndash;0.218).\u003c/p\u003e\u003cp\u003eThere were also significant differences between the LMR values observed in treated coeliac disease and healthy controls, implying that it may take some time before mucosal integrity returns to baseline. A study by Cummins et al. showed (via the L:R test) that gut permeability improves after 2 months on a gluten free diet (GFD), but that it takes up to 6 months before villous recovery is observed\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. Duerksen and colleagues demonstrated that more than 80% of coeliac patients on GFD for at least a year exhibited reduced gut permeability, although permeability only returned to normal levels in 48% of patients (10/21)\u003csup\u003e64\u003c/sup\u003e. Rajani et al. (one of the papers included in this analysis) reported no significant difference in LMR between healthy controls and coeliac patients who followed a GFD for a year\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Similarly, Vogelsang et al. (another paper included in this analysis) also reported no significant difference in LMR when comparing healthy subjects against coeliac patients who had a median of 44 months on a GFD\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. However, LMR values were significantly different (healthy vs. treated coeliac) in the studies published by Vilela et al. (1 year of GFD)\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e and Ukabam et al. (5\u0026ndash;8 months of GFD)\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Thus, current evidence points towards the role of a GFD in improving gut permeability and restoring gut integrity after more than 12 months.\u003c/p\u003e\u003cp\u003eAnother important finding in this review is the presence of significant differences in LMR between healthy controls and both active and inactive Crohn\u0026rsquo;s disease. Moreover, significant differences were also observed between active and inactive Crohn\u0026rsquo;s patients. While the pathogenesis of Crohn\u0026rsquo;s disease is multifactorial and the link to gut permeability is still not well understood, a study in 2019 using three-dimensional tissue culture models demonstrated that epithelial barrier dysfunction may be caused by Tumour Necrosis Factor (TNF)-α induced tight junction modulation and involvement of the c-Jun N-terminal protein kinase mitogen-activated protein kinases (JNK MAPK) signalling pathway\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. Furthermore, altered gut permeability is surmised to be present at the early stages of disease, as increased paracellular permeability was found even in patients with quiescent IBD where endoscopic activity was absent\u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. Techniques other than the L:M test have also been used to assess gut permeability in Crohn\u0026rsquo;s disease. For example, in a recent study, a moderate positive correlation was found between excreted Chromium-52 labelled ethylenediamine tetraacetic acid (\u003csup\u003e52\u003c/sup\u003eCr-EDTA) and faecal calprotectin levels (a known marker of gut permeability) in Crohn\u0026rsquo;s patients\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e. Similarly, the use of zonulin\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e and Ussing chambers\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e have also demonstrated increases in gut permeability in Crohn\u0026rsquo;s disease. Thus, our findings are in agreement with the above studies and provide further evidence for the importance of gut permeability in Crohn\u0026rsquo;s disease.\u003c/p\u003e\u003cp\u003eInterestingly, the differences in LMR between controls, active and inactive Crohn\u0026rsquo;s disease were smaller than those observed for untreated coeliac disease. This may indicate that the breakdown in epithelial barrier function is more pronounced in coeliac disease than it is in Crohn\u0026rsquo;s. Despite this, there was again significant heterogeneity in the difference values observed between control and active Crohn\u0026rsquo;s disease, and between inactive and active Crohn\u0026rsquo;s disease. This further indicates that observations made with the L:M test need to be taken with caution.\u003c/p\u003e\u003cp\u003eThere are many advantages of the L:M test in measuring gut permeability. It is easy to perform, inexpensive and non-invasive. Our data also suggests that this test is associated with high sensitivity, making it a useful tool in screening for coeliac disease. (Sensitivity and specificity analysis was not performed for Crohn\u0026rsquo;s disease as the necessary data was not available in the papers included in our review). The L:M test was the method of choice in the MAL-ED study, which investigated the link between gut permeability and environmental enteropathy in children across 8 countries\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. However, there is great variability in how the test is performed and our meta-analysis has revealed considerable heterogeneity in the results obtained. Interestingly, Ordiz et al. \u0026ndash; who conducted the L:M test in 1669 rural Malawian children \u0026ndash; surmised that the strong direct correlation between percentage lactulose and percentage mannitol excretion does not support the use of mannitol as a normalising factor for lactulose, and that using percentage lactulose excretion alone actually yields more information about gut integrity than LMR\u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e. In addition, L:M measurements performed by Camilleri et al. indicated that LMR at 0\u0026ndash;2 hours may in part reflect colonic permeability and not exclusively small bowel permeability. They have hence recommended that measurements of small bowel permeability using urine collected in the L:M test over 0\u0026ndash;6 hours should be treated with caution\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eWhile there are clear limitations to the L:M test, the quantification of gut permeability in coeliac and Crohn\u0026rsquo;s disease reported here highlights a potential route for clinicians to better understand other gastrointestinal conditions where current diagnostics can be improved. For example, as larger changes in LMR were obtained in coeliac disease than in the Crohn\u0026rsquo;s disease (relative to healthy controls), this implies the possibility to stratify patients according to their gut permeability. Similarly, as differences were observed between treated and untreated patients, this suggests an opportunity to monitor for signs of relapse in a non-invasive manner (i.e. without the need for endoscopy). Thus, quantifying gut permeability may provide an avenue for the practising clinician to better assess patients with FGDs. Indeed, there is promise in utilising gut permeability values to improve management of this complex group of patients in either the primary care setting or the gastroenterology clinic. Nonetheless, we stress that the results of our meta-analysis do not necessarily suggest that the L:M test is currently suitable for this purpose. The high heterogeneity observed across groups and datasets means that it is unlikely that the L:M test will find widespread clinical use in its current form (and indeed explains why it has not done so to date). Hence, if assessment of gut permeability is to find widespread use in the diagnosis of FGDs, Crohn\u0026rsquo;s, coeliac or other conditions then it is highly likely that improved diagnostic tools/methods (or at the very least improved protocols for deployment of the L:M test) will be required.\u003c/p\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eThe main limitation of this meta-analysis is the heterogeneity of our results, which is likely to be explained by the variations in how the L:M test was performed (and by physiological variations across individuals). A list of protocol variations that may have caused the heterogeneity is presented in Table S3. It is also difficult to directly assess the results of the two different solutes used due to the heterogeneity in most of these comparisons. In one of the studies\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, both 5:2 and 2:1 lactulose: mannitol ratios in the solutes were given to patients during the L:M test, making it more difficult to compare the differences in LMR results between the two solutes. Furthermore, most studies that were available and included in the meta-analysis were at significant risk of bias. There are also variations in the way sensitivity and specificity were measured. As shown in Table S4, due to the heterogenous nature of the L:M test, different cut-off point values were used in included studies for diagnosis of disease. There were also not many studies that assessed the value of the L:M test as a screening measure in coeliac or Crohn\u0026rsquo;s disease.\u003c/p\u003e\u003cp\u003eAnother limitation in this meta-analysis is in the variability in how active or inactive Crohn\u0026rsquo;s was defined as evidenced in Table S1. Crucially, however, most of these limitations are inherent to the L:M test itself. Thus, the fact that our results were heterogeneous highlights these important limitations to the L:M test and reveals that improvements are required if it is to be more widely used for clinical assessment of gut permeability.\u003c/p\u003e\u003cp\u003eOverall, this review has quantified the diagnostic value of the L:M test and reported the LMR values in healthy subjects, treated and untreated coeliac disease, and inactive and active Crohn\u0026rsquo;s disease. In addition, it provides a quantification of the heterogeneity in LMR values observed in these disease states. Our analysis demonstrates that there is potential value in measuring gut permeability in both Crohn\u0026rsquo;s and coeliac disease, and it provides an insight into the role of gut permeability in the pathogenesis of both conditions. Importantly, however, it also highlights the limitations in the L:M test and the need for both improved protocols and alternative diagnostic tools.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eGut permeability is significantly impaired in untreated coeliac and Crohn\u0026rsquo;s disease. Gut barrier function is then recovered as patients are treated appropriately. These changes can be observed using the L:M test and this meta-analysis reports pooled LMR values in both diseases. While the L:M test can provide good diagnostic accuracy and offers some insight into gut permeability, it is limited by the lack of standardisation and the length of time required to conduct the test. Thus, if the L:M test is to find wider clinical use, then an optimised, standardised protocol needs to be determined and used. Even if this is achieved, the limited use of the L:M test may persist due to physiological variations between subjects and limitations in the accuracy of the test caused by changes in the permeation of mannitol. As such, there is a strong case for the development of new diagnostic tools that can provide faster, more accurate and more reliable quantification of gut permeability in a minimally or non-invasive manner. Such devices would have potential in monitoring progression/resolution of diseases such as coeliac and Crohn\u0026rsquo;s, and in identifying patients at risk of relapse. There is now an improved understanding of the increasing use of gut permeability analysis in patient care, and as a result, there is a concomitant need for robust evidence to develop this field for its next stage of healthcare innovation.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate: Not applicable\u003c/p\u003e\n\u003cp\u003eConsent for publication: Not applicable\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials: The dataset used and/or analysed during the current study are available from the corresponding author on reasonable request\u003c/p\u003e\n\u003cp\u003eCompeting interests: The authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003eFunding: National Institute for Health Research (NIHR) Imperial Biomedical Research Centre (BRC).\u003c/p\u003e\n\u003cp\u003eAuthor contributions: JG: library search for literature review, data collation, analysis and co-authorship. SN: duplicate assessment of study bias and co-authorship. JT: staff supervisor and co-authorship. AD: staff supervisor and co-authorship. HA: staff supervisor, methodology expert and senior\u0026nbsp;authorship. AT: staff supervisor, methodology expert and senior\u0026nbsp;authorship.\u0026nbsp;HA and AT contributed equally to this work. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eAcknowledgements: This article reports independent research funded by the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre (BRC). The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health. We would also like to acknowledge the contributions of Helen Elwell, the medical librarian, for her help in the literature identification process of the review.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMayer EA, Tillisch K, Gupta A. Gut/brain axis and the microbiota. The Journal of clinical investigation. 2015 Mar 2;125(3):926-38.\u003c/li\u003e\n\u003cli\u003eCamilleri M. Leaky gut: mechanisms, measurement and clinical implications in humans. Gut. 2019 Aug 1;68(8):1516-26.\u003c/li\u003e\n\u003cli\u003eCanavan C, West J, Card T. The epidemiology of irritable bowel syndrome. Clinical epidemiology. 2014;6:71.\u003c/li\u003e\n\u003cli\u003eSequeira IR, Lentle RG, Kruger MC, Hurst RD. Standardising the lactulose mannitol test of gut permeability to minimise error and promote comparability. PloS one. 2014;9(6).\u003c/li\u003e\n\u003cli\u003eParoni R, Fermo I, Molteni L, Folini L, Pastore MR, Mosca A, Bosi E. 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All disease begins in the (leaky) gut: Role of zonulin-mediated gut permeability in the pathogenesis of some chronic inflammatory diseases. F1000Research. 2020;9.\u003c/li\u003e\n\u003cli\u003eThomson A, Smart K, Somerville MS, Lauder SN, Appanna G, Horwood J, Raj LS, Srivastava B, Durai D, Scurr MJ, Keita \u0026Aring;V. The Ussing chamber system for measuring intestinal permeability in health and disease. BMC gastroenterology. 2019 Dec;19(1):98\u003c/li\u003e\n\u003cli\u003eKosek M, Guerrant RL, Kang G, Bhutta Z, Yori PP, Gratz J, Gottlieb M, Lang D, Lee G, Haque R, Mason CJ. Assessment of environmental enteropathy in the MAL-ED cohort study: theoretical and analytic framework. Clinical Infectious Diseases. 2014 Nov 1;59(suppl_4):S239-47.\u003c/li\u003e\n\u003cli\u003eOrdiz MI, Davitt C, Stephenson K, Agapova S, Divala O, Shaikh N, Manary MJ. EB 2017 Article: Interpretation of the lactulose: mannitol test in rural Malawian children at risk for perturbations in intestinal permeability. Experimental Biology and Medicine. 2018 May;243(8):677-83.\u003c/li\u003e\n\u003cli\u003eCamilleri M, Nadeau A, Lamsam J, Linker Nord S, Ryks M, Burton D, Sweetser S, Zinsmeister AR, Singh R. Understanding measurements of intestinal permeability in healthy humans with urine lactulose and mannitol excretion. Neurogastroenterology \u0026amp; Motility. 2010 Jan;22(1):e15-26.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Coeliac, Crohn’s Disease, Lactulose Mannitol test, Gut Permeability","lastPublishedDoi":"10.21203/rs.3.rs-257838/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-257838/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eA widely used method in assessing small bowel permeability is the lactulose:mannitol test, where the lactulose:mannitol ratio (LMR) is measured. However, there is discrepancy in how the test is conducted and in the values of LMR obtained across studies. This meta-analysis aims to determine LMR in healthy subjects, coeliac and Crohn\u0026rsquo;s disease.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA literature search was performed using PRISMA guidance to identify studies assessing LMR in coeliac or Crohn\u0026rsquo;s disease. 19 studies included in the meta-analysis measured gut permeability in coeliac disease, 17 studies in Crohn\u0026rsquo;s disease. Outcomes of interest were LMR values and comparisons of standard mean difference (SMD) and weighted mean difference (WMD) in healthy controls, inactive Crohn\u0026rsquo;s, active Crohn\u0026rsquo;s, treated coeliac and untreated coeliac. Pooled estimates of differences in LMR were calculated using the random effects model.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003ePooled LMR in healthy controls was 0.014 (95% CI: 0.006\u0026ndash;0.022) while pooled LMRs in untreated and treated coeliac were 0.133 (95% CI: 0.089\u0026ndash;0.178) and 0.037 (95% CI: 0.019\u0026ndash;0.055). In active and inactive Crohn\u0026rsquo;s disease, pooled LMRs were 0.093 (95% CI: 0.031\u0026ndash;0.156) and 0.028 (95% CI: 0.015\u0026ndash;0.041). Significant differences were observed in LMR between: (i) healthy controls and treated coeliacs (SMD\u0026thinsp;=\u0026thinsp;0.409 95% CI 0.034 to 0.783, p\u0026thinsp;=\u0026thinsp;0.032), (ii) healthy controls and untreated coeliacs (SMD\u0026thinsp;=\u0026thinsp;1.362 95% CI: 0.740 to 1.984, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), (iii) treated coeliacs and untreated coeliacs (SMD\u0026thinsp;=\u0026thinsp;0.722 95% CI: 0.286 to 1.157, p\u0026thinsp;=\u0026thinsp;0.001), (iv) healthy controls and inactive Crohns (SMD\u0026thinsp;=\u0026thinsp;1.265 95% CI: 0.845 to 1.686, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), (v) healthy controls and active Crohns (SMD\u0026thinsp;=\u0026thinsp;2.868 95% CI: 2.112 to 3.623, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and (vi) active Crohns and inactive Crohns (SMD\u0026thinsp;=\u0026thinsp;1.429 (95% CI: 0.580 to 2.278, p\u0026thinsp;=\u0026thinsp;0.001). High heterogeneity was observed, which was attributed to variability in protocols used across different studies.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe use of gut permeability measurements in screening and monitoring of coeliac and Crohn\u0026rsquo;s disease is promising. LMR is useful in performing this function with significant limitations. More robust alternative tests with higher degrees of clinical evidence are needed if measurements of gut permeability are to find widespread clinical use.\u003c/p\u003e\u003ch2\u003eTrial Registration\u003c/h2\u003e \u003cp\u003eNot Applicable\u003c/p\u003e","manuscriptTitle":"A case for improved assessment of gut permeability – a meta-analysis quantifying the lactulose:mannitol ratio in coeliac and Crohn’s disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-02-25 21:50:50","doi":"10.21203/rs.3.rs-257838/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorAssigned","content":"","date":"2021-02-10T00:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-02-09T23:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-02-09T23:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"","date":"2021-02-09T00:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"03a5cf20-64a9-4e6c-baed-350fdaf1f159","owner":[],"postedDate":"February 25th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":2599311,"name":"Gastroenterology \u0026 Hepatology"}],"tags":[],"updatedAt":"2022-01-10T13:52:05+00:00","versionOfRecord":{"articleIdentity":"rs-257838","link":"https://doi.org/10.1186/s12876-021-02082-z","journal":{"identity":"bmc-gastroenterology","isVorOnly":false,"title":"BMC Gastroenterology"},"publishedOn":"2022-01-10 13:52:05","publishedOnDateReadable":"January 10th, 2022"},"versionCreatedAt":"2021-02-25 21:50:50","video":"","vorDoi":"10.1186/s12876-021-02082-z","vorDoiUrl":"https://doi.org/10.1186/s12876-021-02082-z","workflowStages":[]},"version":"v1","identity":"rs-257838","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-257838","identity":"rs-257838","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}