Suspected blood indicator in capsule endoscopy: a valuable tool for gastrointestinal bleeding diagnosis

Carvalho, Pedro Boal; Magalhães, Joana; Castro, Francisca Dias de; Monteiro, Sara; Rosa, Bruno; Moreira, Maria João; Cotter, José

doi:10.1590/s0004-2803.2017v54n1-03

Cited by 23 publications

(7 citation statements)

References 23 publications

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“…These results are in accordance with our results. False negative results of CE can occur due to the limited visual field of CE, poor bowel preparation, inadequate luminal distention, rapid passage around the proximal small bowel, and the lesions where bleeding has stopped spontaneously during CE [26,27]. It implies that negative findings in both, CT and CE, in patients with OGIB, do not guarantee lower rebleeding rates during long term follow-up.…”

Section: Discussionmentioning

confidence: 99%

Clinical Outcomes between P1 and P0 Lesions for Obscure Gastrointestinal Bleeding with Negative Computed Tomography and Capsule Endoscopy

et al. 2021

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Background: A simple classification for the relevance of lesions (P0, P1, and P2; no bleeding potential, less likely to bleed, and more likely to bleed, respectively) based on capsule endoscopy (CE) findings has been used. This study aimed at investigating rebleeding rates and predictive factors of P0 and P1 lesions after obtaining negative findings in both, CE and computed tomography (CT), for patients with obscure gastrointestinal bleeding (OGIB). Methods: Among 193 patients resulted in negative CE findings defined as P0 or P1 lesions, 84 patients with negative results on CT images were enrolled in this study. The rebleeding rates and predictive factors were assessed in the P0 and P1 groups. Results: Overall rebleeding rate in patients with negative CT and CE was 17.9%; 18.4% in the P0 group; 17.4% in the P1 group within a median follow-up duration of 18.5 months. In the P0 and P1 groups, the cumulative rebleeding rates were 9.2%, 25.4%, and 25.4%, and 6.9%, 11.8%, and 18.6% at 12, 24, and 60 months, respectively (p = 0.97). There were no independent rebleeding associated factors in the P0 group, whereas Charlson comorbidity index (CCI) (hazard ratio (HR) = 2.019, 95% confidence interval (CI): 1.158–3.519, p = 0.013), and initial low hemoglobin (Hb) level (<8 g/dL) (HR = 15.085, 95% CI: 1.182–192.514, p = 0.037) were independent predictive factors responsible for rebleeding in the P1 group. Conclusions: Despite having negative findings on CT and CE, patients with OGIB have a significant potential rebleeding risk. Although there was no significant difference in rebleeding rates between the P0 and P1 groups on CE, the P1 group, with CCI or low initial Hb level, should be cautiously observed after the first bleeding episode.

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Section: Discussionmentioning

confidence: 99%

Clinical Outcomes between P1 and P0 Lesions for Obscure Gastrointestinal Bleeding with Negative Computed Tomography and Capsule Endoscopy

et al. 2021

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“…Therefore, it remains unclear whether UCEIS could be accurately and reproducibly graded by CCE2. In contrast, CSUC has been validated for CCE2, and an automatic analysis system can be utilized to determine the location of bleeding in the colon and detect the bleeding using an SBI 25 . CSUC takes advantage of these characteristics of CCE2 and is expected to be objective and easy to use for clinical practice.…”

Section: Discussionmentioning

confidence: 99%

Determining the usefulness of Capsule Scoring of Ulcerative Colitis in predicting relapse of inactive ulcerative colitis

Matsubayashi

Okabayashi

Nakano

et al. 2020

J of Gastro and Hepatol

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Background and Aim: The usefulness of second-generation colon capsule endoscopy (CCE2) in ulcerative colitis (UC), especially in clinically inactive patients, has been reported. Capsule Scoring of Ulcerative Colitis (CSUC) was developed as a severity index for UC. We aimed to determine whether CSUC is useful for predicting relapse during clinical remission. Methods: Forty-one UC patients in clinical remission who underwent CCE2 were prospectively registered from April 2016 to August 2019. Patients' CSUC score was obtained; those with subsequent relapse were followed up retrospectively. The correlation of CSUC with white blood cell count, platelet count, albumin, C-reactive protein, fecal calprotectin and fecal lactoferrin levels, and fecal immunochemical test results was evaluated; their predictive values for future relapse were compared. Results: The correlations of CSUC with white blood cell, platelet, albumin, C-reactive protein, fecal calprotectin, fecal immunochemical test, and fecal lactoferrin values were r s = 0.13, 0.27, À0.25, 0.15, 0.50, 0.43, and 0.50, respectively. CSUC was higher in 12 patients who relapsed within 1 year than in 29 patients who remained in clinical remission (2.83 ± 1.95 vs 0.72 ± 1.00, P < 0.01). Receiver operator characteristic curve analysis showed that CSUC ≥ 1 was a predictor of relapse (area under the curve of 0.82, sensitivity of 83.3%, specificity of 58.6%) and maybe superior to fecal biomarkers. In the univariate analysis, patients with CSUC of 0 had a lower relapse rate than those with CSUC of ≧ 1 (P = 0.03, log-rank test). After analyzing patients who underwent CCE2 within 6 months after the successful induction treatment, results showed that those with CSUC of ≤ 1 remained in clinical remission for a year. Conclusion: CSUC predicts relapse within 1 year in UC patients in clinical remission, especially when used 6 months after induction treatment.

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“…Small intestinal bleeds are the most frequent indication for the use of VCE. Although commercially available reading systems include blood content enhancement algorithms, referred to as “suspected blood indicators” (SBIs), the false positive rate is still high at over 70% [ 88 ]. Xiao et al and Hassan et al developed AI algorithms for the detection of bleeds with high sensitivity and specificity (99%) [ 23 , 89 ].…”

Section: Duodenal and Small Intestinal Lesionsmentioning

confidence: 99%

A New Dawn for the Use of Artificial Intelligence in Gastroenterology, Hepatology and Pancreatology

2021

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Artificial intelligence (AI) is rapidly becoming an essential tool in the medical field as well as in daily life. Recent developments in deep learning, a subfield of AI, have brought remarkable advances in image recognition, which facilitates improvement in the early detection of cancer by endoscopy, ultrasonography, and computed tomography. In addition, AI-assisted big data analysis represents a great step forward for precision medicine. This review provides an overview of AI technology, particularly for gastroenterology, hepatology, and pancreatology, to help clinicians utilize AI in the near future.

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Suspected blood indicator in capsule endoscopy: a valuable tool for gastrointestinal bleeding diagnosis

Cited by 23 publications

References 23 publications

Clinical Outcomes between P1 and P0 Lesions for Obscure Gastrointestinal Bleeding with Negative Computed Tomography and Capsule Endoscopy

Clinical Outcomes between P1 and P0 Lesions for Obscure Gastrointestinal Bleeding with Negative Computed Tomography and Capsule Endoscopy

Determining the usefulness of Capsule Scoring of Ulcerative Colitis in predicting relapse of inactive ulcerative colitis

A New Dawn for the Use of Artificial Intelligence in Gastroenterology, Hepatology and Pancreatology

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