Assessing Severity of Disease in Patients with Ulcerative Colitis
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SUBMITTER: Pabla B
PROVIDER: S-EPMC7510557 | biostudies-literature | 2020 Sep
REPOSITORIES: biostudies-literature
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Project description:BackgroundColonoscopy [CS] is the standard for assessing disease activity in ulcerative colitis [UC], although invasive and poorly tolerated. Bowel ultrasound [BUS] may be a valid alternative in UC patients; however, the comparative accuracy between BUS and CS is unknown.MethodsConsecutive patients with UC were prospectively assessed by CS and BUS. Colonic wall thickening [CWT >3 mm], colonic wall flow at power Doppler [CWF], colonic wall pattern [CWP], and presence of lymph nodes evaluated at BUS were compared with CS. The endoscopic activity was assessed according to the Mayo endoscopic sub-score [0-3]. All BUS investigations were performed by two independent gastroenterologists and the kappa statistic for agreement was calculated. Ultrasonography-based criteria (Humanitas Ultrasound Criteria [HUC]) were developed.ResultsA total of 53 UC patients [56% with left-sided colitis, 19% with pancolitis] were prospectively enrolled. Of these, 22 patients had mucosal healing [Mayo endoscopic sub-score 0-1] and 31 patients were in endoscopic activity. CWT, CWF, hypoechogenic CWP and the presence of lymph nodes significantly correlated with endoscopic activity [p < 0.05]. CWT [p = 0.01] and CWF [p = 0.09] were independent predictors for endoscopic activity. The HUC developed are: [i] the presence of a CWF and CWT > 3 mm; or [ii] the absence of a CWF and CWT > 4.43 mm. They showed high accuracy for the detection of disease activity [sensitivity 0.71, specificity 1.00]. The interobserver agreement for BUS was excellent [kappa 0.86].ConclusionsBUS is a non-invasive, easy-to-use tool to manage UC patients in clinical practice. HUC were very accurate in assessing disease activity in UC patients.
| S-EPMC6260119 | biostudies-literature
Project description:PurposeUlcerative colitis (UC) is an inflammatory bowel disease with an unclear etiology that can lead to irreversible changes in distal colonic function in chronic patients. This study investigated anorectal function in recurrent UC patients and identified influencing factors.MethodsThis prospective study enrolled 33 recurrent UC patients and 40 newly diagnosed patients from January 2019 to December 2022. Data collection included clinical records, scores, and anorectal function assessments. Regression analyses were used to identify factors impacting anorectal function.ResultsRecurrent UC patients had higher baseline CRP and fecal calprotectin levels, increased anxiety and depression, and more severe fecal incontinence. They also had lower BMIs, serum Hb and albumin (ALB) levels, and Inflammatory Bowel Disease Questionnaire scores than did initial-onset UC patients. Multivariate linear regression analysis revealed that long disease duration (coef. - 0.376, P < 0.001) and high fecal calprotectin level (coef. - 0.656, P < 0.001) independently influenced the initial sensation threshold in recurrent UC patients. Additionally, high fecal calprotectin (coef. - 0.073, P = 0.013) and high Zung Self-Rating Anxiety Scale score (coef. - 0.489, P = 0.001) were identified as two independent determinants of the defecation volume threshold. For the defecation urgency threshold, the independent factors included high disease duration (coef. - 0.358, P = 0.017) and high fecal calprotectin level (coef. - 0.499, P = 0.001). Similarly, the sole independent factor identified for the maximum capacity threshold was high fecal calprotectin (coef. - 0.691, P = 0.001).ConclusionRecurrent UC patients had increased rectal sensitivity and compromised anorectal function, which significantly impacted quality of life. Proactively managing the disease, reducing UC relapses, and addressing anxiety are effective measures for improving anorectal function in these patients.
| S-EPMC11249410 | biostudies-literature
Project description:BackgroundUlcerative colitis is a heterogeneous disease in terms of disease course, location, and therapeutic response. The current study was done to assess the alteration of the gut microbiome in UC patients and its relationship to severity, response to therapy, and outcome.Patients and methodsThe study included 96 participants who were divided into a case group (n = 48, recent onset, treatment naive ulcerative colitis patients who were subdivided into mild, moderate, and severe subgroups based on Truelove-Witts and endoscopic severity) and a healthy control group (n = 48). All were subjected to a thorough history, clinical examination, colonoscopy, routine laboratory tests, and quantitative real-time PCR to quantify Bacteroides, Lactobacilli, Faecalibacterium prausnitzii, Veillonella, and Hemophilus in fecal samples at baseline and 6 months after treatment.ResultsBacterial 16S rRNA gene sequencing revealed a significant reduction in the phylum Firmicutes in UC patients, with a significant predominance of the phylum Bacteriodetes. F. prausnitzii and lactobacilli were inversely proportional to disease severity, whereas Bacteroides, Hemophilus, and Veillonella were directly proportional to it. Six months after therapy, a statistically significant increase in F. prausnitzii and lactobacilli was observed, with a decrease in the levels of other bacteria. Lower baseline F. praustinizii (< 8.5) increased the risk of relapse; however, lower ESR (< 10), lower post-treatment CRP (< 6), lower Bacteroides (< 10.6) indefinitely protect against relapse.ConclusionThe gut microbiome of recently diagnosed UC showed lower levels of Lactobacilli, Faecalibacterium, and higher levels of Bacteroides and Veillonella, and the change in their levels can be used to predict response to therapy.
| S-EPMC10460709 | biostudies-literature
Project description:Significant gut microbiota heterogeneity exists amongst UC patients though the clinical implications of this variance are unknown. European and South Asian UC patients exhibit distinct disease risk alleles, many of which regulate immune function and relate to variation in gut microbiota β-diversity. We hypothesized ethnically distinct UC patients exhibit discrete gut microbiotas with unique luminal metabolic programming that influence adaptive immune responses and relate to clinical status. Using parallel bacterial 16S rRNA and fungal ITS2 sequencing of fecal samples (UC n=30; healthy n=13), we corroborated previous observations of UC-associated depletion of bacterial diversity and demonstrated significant gastrointestinal expansion of Saccharomycetales as a novel UC characteristic. We identified four distinct microbial community states (MCS 1-4), confirmed their existence using microbiota data from an independent UC cohort, and show they co-associate with patient ethnicity and degree of disease severity. Each MCS was predicted to be uniquely enriched for specific amino acid, carbohydrate, and lipid metabolism pathways and exhibited significant luminal enrichment of metabolic products from these pathways. Using a novel in vitro human DC/T-cell assay we show that DC exposure to patient fecal water led to MCS -specific changes in T-cell populations, particularly the Th1:Th2 ratio, and that patients with the most severe disease exhibited the greatest Th2 skewing. Thus, based on ethnicity, microbiome composition, and associated metabolic dysfunction, UC patients may be stratified in a clinically and immunologically meaningful manner, providing a platform for the development of FMC-focused therapy. Fecal microbiome was assessed with Affymetrix PhyloChip arrays from patients with ulcerative colitis and healthy controls.
2016-07-25 | E-GEOD-78724 | biostudies-arrayexpress
Project description:BackgroundVariability in endoscopic assessment necessitates rigorous investigation of descriptors for scoring severity of ulcerative colitis (UC).ObjectiveTo evaluate variation in the overall endoscopic assessment of severity, the intra- and interindividual variation of descriptive terms and to create an Ulcerative Colitis Endoscopic Index of Severity which could be validated.DesignA two-phase study used a library of 670 video sigmoidoscopies from patients with Mayo Clinic scores 0-11, supplemented by 10 videos from five people without UC and five hospitalised patients with acute severe UC. In phase 1, each of 10 investigators viewed 16/24 videos to assess agreement on the Baron score with a central reader and agreed definitions of 10 endoscopic descriptors. In phase 2, each of 30 different investigators rated 25/60 different videos for the descriptors and assessed overall severity on a 0-100 visual analogue scale. κ Statistics tested inter- and intraobserver variability for each descriptor. A general linear mixed regression model based on logit link and β distribution of variance was used to predict overall endoscopic severity from descriptors.ResultsThere was 76% agreement for 'severe', but 27% agreement for 'normal' appearances between phase I investigators and the central reader. In phase 2, weighted κ values ranged from 0.34 to 0.65 and 0.30 to 0.45 within and between observers for the 10 descriptors. The final model incorporated vascular pattern, (normal/patchy/complete obliteration) bleeding (none/mucosal/luminal mild/luminal moderate or severe), erosions and ulcers (none/erosions/superficial/deep), each with precise definitions, which explained 90% of the variance (pR(2), Akaike Information Criterion) in the overall assessment of endoscopic severity, predictions varying from 4 to 93 on a 100-point scale (from normal to worst endoscopic severity).ConclusionThe Ulcerative Colitis Endoscopic Index of Severity accurately predicts overall assessment of endoscopic severity of UC. Validity and responsiveness need further testing before it can be applied as an outcome measure in clinical trials or clinical practice.
| S-EPMC3292713 | biostudies-literature
Project description:Despite significant evidence that the expression of several microRNAs (miRNAs) impacts disease activity in patients with ulcerative colitis (UC), it remains unknown if the more severe disease phenotype seen in pediatric onset UC can be explained by an altered miRNA expression. In this study, we assessed the relationship between miRNA expression, age, and disease severity in pediatric and adult patients with UC. Using RT-qPCR, we analyzed the expression of miR-21, miR-31, miR-126, miR-142 and miR-155 in paraffin embedded rectum biopsies from 30 pediatric and 30 adult-onset UC patients. We found that lesions from adult patients had significantly higher expression levels of miR-21 compared to pediatric patients and that the expression levels of miR-31 (all patients) and miR-155 (pediatric patients only) correlated inversely with histological assessed disease severity. Using in situ hybridization followed by image analysis, the expression level estimates of miR-21 and miR-126 correlated with histological assessed disease severity. In conclusion, we found that the expression of miRNAs depends on the age of the patient and/or the severity of the disease, suggesting that miRNAs may contribute to the regulation of inflammation in UC and could be useful biomarkers in the surveillance of disease severity.
| S-EPMC7993741 | biostudies-literature
Project description:Significant gut microbiota heterogeneity exists amongst UC patients though the clinical implications of this variance are unknown. European and South Asian UC patients exhibit distinct disease risk alleles, many of which regulate immune function and relate to variation in gut microbiota β-diversity. We hypothesized ethnically distinct UC patients exhibit discrete gut microbiotas with unique luminal metabolic programming that influence adaptive immune responses and relate to clinical status. Using parallel bacterial 16S rRNA and fungal ITS2 sequencing of fecal samples (UC n=30; healthy n=13), we corroborated previous observations of UC-associated depletion of bacterial diversity and demonstrated significant gastrointestinal expansion of Saccharomycetales as a novel UC characteristic. We identified four distinct microbial community states (MCS 1-4), confirmed their existence using microbiota data from an independent UC cohort, and show they co-associate with patient ethnicity and degree of disease severity. Each MCS was predicted to be uniquely enriched for specific amino acid, carbohydrate, and lipid metabolism pathways and exhibited significant luminal enrichment of metabolic products from these pathways. Using a novel in vitro human DC/T-cell assay we show that DC exposure to patient fecal water led to MCS -specific changes in T-cell populations, particularly the Th1:Th2 ratio, and that patients with the most severe disease exhibited the greatest Th2 skewing. Thus, based on ethnicity, microbiome composition, and associated metabolic dysfunction, UC patients may be stratified in a clinically and immunologically meaningful manner, providing a platform for the development of FMC-focused therapy.
2016-07-25 | GSE78724 | GEO
Project description:BackgroundThe significance of endoscopic evaluation in the diagnosis and management of ulcerative colitis (UC) has been widely recognized. Over the years, scholars have established several endoscopic scores. Herein, we assessed the clinical application value of the Mayo Endoscopic Subscore (Mayo ES), the Degree of Ulcerative Colitis Burden of Luminal Inflammation (DUBLIN) score, and the Ulcerative Colitis Endoscopic Index of Severity (UCEIS) score in UC patients, by comparing their correlation with disease activity and their predictive potential for treatment response and clinical outcomes.MethodsUC patients hospitalized from September 2015 to September 2019 were retrospectively analysed. We employed Spearman's rank correlation coefficient to assess the linear association of the assessed endoscopic scores with the clinical parameters. The receiver-operating characteristic curve was applied to evaluate the predictive capabilities of the endoscopic scores for treatment escalation and 1-year readmission.ResultsA total of 178 patients were enrolled; most of them (82%) suffered moderate or severe colitis. Among them, 48 (27%) patients received treatment escalation and 59 (33%) were readmitted within 1 year. The DUBLIN and UCEIS scores demonstrated higher correlations with clinical parameters than the Mayo ES. The DUBLIN scores significantly differed between patients with mild, moderate, and severe colitis (all P < 0.001). The UCEIS scores demonstrated the best predictabilities for treatment escalation and 1-year readmission with an area under the curve of 0.88 and 0.75, respectively. Compared to the UCEIS and DUBLIN scores, the predictive capabilities of the Mayo ES for treatment escalation (both P < 0.001) and 1-year readmission (P < 0.001 and P = 0.002, respectively) were lower. The UCEIS scores exhibited a significant difference between the steroid-responsive group and the steroid-dependent or steroid-refractory group (both P < 0.001), while no significant differences in the Mayo ES and DUBLIN scores were found among the three groups (both P > 0.05).ConclusionThis study demonstrates that both the DUBLIN and UCEIS scores outperform the Mayo ES in assessing disease severity and predicting treatment response and clinical outcomes in UC patients.
| S-EPMC8677544 | biostudies-literature
Project description:UNLABELLED:Significant gut microbiota heterogeneity exists among ulcerative colitis (UC) patients, though the clinical implications of this variance are unknown. We hypothesized that ethnically distinct UC patients exhibit discrete gut microbiotas with unique metabolic programming that differentially influence immune activity and clinical status. Using parallel 16S rRNA and internal transcribed spacer 2 sequencing of fecal samples (UC, 30; healthy, 13), we corroborated previous observations of UC-associated bacterial diversity depletion and demonstrated significant Saccharomycetales expansion as characteristic of UC gut dysbiosis. Furthermore, we identified four distinct microbial community states (MCSs) within our cohort, confirmed their existence in an independent UC cohort, and demonstrated their coassociation with both patient ethnicity and disease severity. Each MCS was uniquely enriched for specific amino acid, carbohydrate, and lipid metabolism pathways and exhibited significant luminal enrichment of the metabolic products of these pathways. Using a novel ex vivo human dendritic cell and T-cell coculture assay, we showed that exposure to fecal water from UC patients caused significant Th2 skewing in CD4(+) T-cell populations compared to that of healthy participants. In addition, fecal water from patients in whom their MCS was associated with the highest level of disease severity induced the most dramatic Th2 skewing. Combined with future investigations, these observations could lead to the identification of highly resolved UC subsets based on defined microbial gradients or discrete microbial features that may be exploited for the development of novel, more effective therapies. IMPORTANCE:Despite years of research, the etiology of UC remains enigmatic. Diagnosis is difficult and the patient population heterogeneous, which represents a significant barrier to the development of more effective, tailored therapy. In this study, we demonstrate the clinical utility of the gut microbiome in stratifying UC patients by identifying the existence of four distinct interkingdom pathogenic microbiotas within the UC patient population that are compositionally and metabolically distinct, covary with clinical markers of disease severity, and drive discrete CD4(+) T-cell expansions ex vivo These findings offer new insight into the potential value of the gut microbiome as a tool for subdividing UC patients, opening avenues to the development of more personalized treatment plans and targeted therapies.
| S-EPMC4992973 | biostudies-literature
Project description:ImportanceAssessing endoscopic disease severity in ulcerative colitis (UC) is a key element in determining therapeutic response, but its use in clinical practice is limited by the requirement for experienced human reviewers.ObjectiveTo determine whether deep learning models can grade the endoscopic severity of UC as well as experienced human reviewers.Design, setting, and participantsIn this diagnostic study, retrospective grading of endoscopic images using the 4-level Mayo subscore was performed by 2 independent reviewers with score discrepancies adjudicated by a third reviewer. Using 16 514 images from 3082 patients with UC who underwent colonoscopy at a single tertiary care referral center in the United States between January 1, 2007, and December 31, 2017, a 159-layer convolutional neural network (CNN) was constructed as a deep learning model to train and categorize images into 2 clinically relevant groups: remission (Mayo subscore 0 or 1) and moderate to severe disease (Mayo subscore, 2 or 3). Ninety percent of the cohort was used to build the model and 10% was used to test it; the process was repeated 10 times. A set of 30 full-motion colonoscopy videos, unseen by the model, was then used for external validation to mimic real-world application.Main outcomes and measuresModel performance was assessed using area under the receiver operating curve (AUROC), sensitivity and specificity, positive predictive value (PPV), and negative predictive value (NPV). Kappa statistics (κ) were used to measure agreement of the CNN relative to adjudicated human reference cores.ResultsThe authors included 16 514 images from 3082 unique patients (median [IQR] age, 41.3 [26.1-61.8] years, 1678 [54.4%] female), with 3980 images (24.1%) classified as moderate-to-severe disease by the adjudicated reference score. The CNN was excellent for distinguishing endoscopic remission from moderate-to-severe disease with an AUROC of 0.966 (95% CI, 0.967-0.972); a PPV of 0.87 (95% CI, 0.85-0.88) with a sensitivity of 83.0% (95% CI, 80.8%-85.4%) and specificty of 96.0% (95% CI, 95.1%-97.1%); and NPV of 0.94 (95% CI, 0.93-0.95). Weighted κ agreement between the CNN and the adjudicated reference score was also good for identifying exact Mayo subscores (κ = 0.84; 95% CI, 0.83-0.86) and was similar to the agreement between experienced reviewers (κ = 0.86; 95% CI, 0.85-0.87). Applying the CNN to entire colonoscopy videos had similar accuracy for identifying moderate to severe disease (AUROC, 0.97; 95% CI, 0.963-0.969).Conclusions and relevanceThis study found that deep learning model performance was similar to experienced human reviewers in grading endoscopic severity of UC. Given its scalability, this approach could improve the use of colonoscopy for UC in both research and routine practice.
| S-EPMC6537821 | biostudies-literature