Gastro Esophageal RefluxNCT04268719
Near Focus NBI-Driven Artificial Intelligence for the Diagnosis of Gastro-Oesophageal Reflux Disease
An observational study of Gastro Esophageal Reflux, run by King's College Hospital NHS Trust at 1 site in United Kingdom.
Trial summary
Gastro-oesophageal reflux disease (GORD) is a chronic condition with symptoms arising secondary to the reflux of stomach contents (Vakil et al., 2006). It is divided into four phenotypes: Erosive Oesophagitis (EO), Non-Erosive Reflux Disease (NERD), Reflux Hypersensitivity (RH), Functional Heartburn (FH) (Nikaki… Read more about this study
- Who is it for?
- Ages 18 to 90 years
- Conditions the study is for
- Gastro Esophageal Reflux
- What is being tested?
- wireless pH capsule recording
- Type of treatment
- Pill or oral medicine
- How many people
- 76 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 23 Nov 2017to 30 Nov 2018
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 90 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Consecutive patients attending the Gastroenterology department for the investigation of symptoms suggestive of Gastro-Oesophageal Reflux Disease (GORD) were approached for recruitment. Patients had to have symptoms including heartburn, regurgitation or chest/epigastric pain for a minimum of 3 months.
Who may be able to join
- Retaining capacity and medically fit for gastroscopy
- Requiring gastroscopy by current BSG guidelines for the investigation of acid reflux/ dyspepsia
Who cannot join
- Unable to give informed consent
- History of oesophageal or gastric surgery
- Allergy to proton-pump inhibitor
- Known Barrett's Oesophagus/ oesophageal carcinoma/ oesophageal stricture/ known oesophageal dysmotility
- Portal Hypertension
- Pacemaker (BRAVO)
Trial locations and contacts
1 site in 1 country.
About this study
Gastro-oesophageal reflux disease (GORD) is a chronic condition with symptoms arising secondary to the reflux of stomach contents (Vakil et al., 2006). It is divided into four phenotypes: Erosive Oesophagitis (EO), Non-Erosive Reflux Disease (NERD), Reflux Hypersensitivity (RH), Functional Heartburn (FH) (Nikaki, Woodland and Sifrim, 2016). The definition of these phenotype have evolved with the addition of diagnostic tests and methods of their interpretation, the most recent being the Lyon Consensus Statement (Gyawali et al., 2018). The majority of patients presenting with symptoms suggestive of GORD have no mucosal lesion seen at endoscopy (Nikaki, Woodland and Sifrim, 2016). Studies have shown a relation of increased IPCL numbers with GORD. This study aims to build a fully autmoated AI model using Near-Focus NBI images on patients with symptoms suggestive of GORD phenotyped in accordance with the Lyon Consensus.
Read the detailed description
Gastro-oesophageal reflux disease (GORD) is a chronic condition with symptoms arising secondary to the reflux of stomach contents (Vakil et al., 2006). It is divided into four phenotypes: Erosive Oesophagitis (EO), Non-Erosive Reflux Disease (NERD), Reflux Hypersensitivity (RH), Functional Heartburn (FH) (Nikaki, Woodland and Sifrim, 2016). The definition of these phenotype have evolved with the addition of diagnostic tests and methods of their interpretation, the most recent being the Lyon Consensus Statement (Gyawali et al., 2018). The majority of patients presenting with symptoms suggestive of GORD have no mucosal lesion seen at endoscopy (Nikaki, Woodland and Sifrim, 2016). Complications of GORD, such as peptic stricture and Barrett's oesophagus, can be readily diagnosed using WLE. The diagnosis of reflux oesophagitis with standard-definition WLE is well described in the Los Angeles (LA) classification (Armstrong et al., 1996) and validated (Lundell et al., 1999) with LA grades C and D confirmatory of GORD (Gyawali et al., 2018). Furthermore, AET is demonstrated to increase with LA classification A to D (Lundell et al., 1999). There is, however, only a modest inter-observer agreement between LA grades (Kappa coefficient 0.4), especially A and B. Furthermore LA grade A oesophagitis is detected in up to 17.0% of asymptomatic patients (Nozu and Komiyama, 2008; Zagari et al., 2008). A diagnosis of GORD and decisions for anti-reflux surgery cannot be made on this basis, mandating pH testing to confirm GORD.
Narrow Band Imaging
Imaging of the gastro-oesophageal junction using high definition Olympus H260 scope using the LA classification of GORD with WLE and NBI demonstrated improvement in overall interobserver reproducibility when used in a combination compared with WLE alone; k 0.62 vs 0.45 (<0.05)(Lee et al., 2007). Features identified using digital magnification NBI at the squamo-columnar junction in cases of EO (n=41; LA grade A and B), NERD (n=36) and controls (n=32) include micro-erosions (100% EO; 52.8% NERD; 23.3% controls), increased vascularity (95.1% EO; 91.7% NERD; 36.7% controls) and round pit patterns (4.9% EO; 5.6% NERD; 70% controls). Increased vascularity combined with absence of round pit pattern distinguishes NERD from controls with sensitivity and specificity 86.1% and 83.3%. Inter-observer agreement in this single centre study was good for increased vascularity (k=0.95) and micro erosions (k=0.89) but low for pit pattern (k=0.59) (Fock et al., 2009).
Intra-papillary capillary loops (IPCLs) are mucosal capillaries arising from the submucosal vein to the papilla, usually arranged in a regular 'dot' like fashion approximately 100micrometres apart (Inoue, 2001). The visualisation of oesophageal IPCLs with NBI is well documented and form the basis of a NBI classification for squamous neoplasia (Inoue et al., 2015). IPCL morphology changes have been proposed in patients being investigated for NERD, in particular dilatation and elongation of IPCLs in patients with NERD with magnification NBI (Kato et al., 2006).
NBI with optical magnification for the diagnosis of GORD has been evaluated in 2 studies (Sharma et al., 2007; Lv et al., 2013). Sharma et al performed a feasibility trial with Olympus Q240Z with quadrantic examination of the distal 5cm by WLE then NBI in n=50 GORD (EO n=30; NERD n=20) and controls (n=30). Similar to Fock et al, the presence of microerosions and hypervascularity was significantly higher amongst GORD. IPCL number and morphology of tortuosity, dilatation were seen significantly more in GORD versus control. These findings were consistent in independent comparison of EO and NERD versus controls. ROC analysis thresholds for best sensitivity and specificity (respectively) for NERD were maximum ipcl/field 131 (90%, 70%), min 99 (85%, 70%) and average 117 (90%, 70%) (Sharma et al., 2007).
Lv et al used the Olympus GIF-H260Z to evaluate NERD (n=40), EO (n=40), Barrett's (n=40) and healthy controls (n=40). IPCL number, morphology (prolonged/dilated/tortuous), microerosions, round pit pattern above or below the SCJ, were recorded as features of reflux. Significant differences were found with increased IPCL number, microerosions, non-round pit patterns below the SCJ in GERD (NERD/EO and BE) patients compared to controls and fewer microerosions in NERD patients compared to RE (Lv et al., 2013).
The definition of NERD in all studies to date, however, is variable and largely based on symptom evaluation, response to PPI and the absence of mucosal lesions at endoscopic examination without standardisation using pH studies.
Artificial Intelligence
To date there is one study evaluating the use of ANNs in predicting GORD based on 45 variables including demographics, medical history, health status, symptoms scores. All patients underwent OGD, 24-pH studies performed in those with no mucosal lesion at endoscopy: 103 GORD patient (62 with reflux oesophagitis and 41 with AET>5%) and n=56 FH patients GORD. The ANN demonstrated an accuracy of 100% compared to 78% using conventional statistical regression analysis (Pace et al., 2005). While these are optimistic findings, the proportion of training and test data used was not specified and further evaluation with larger datasets is clearly warranted. There are no image-driven AI models for the diagnosis of GORD to date. Machine learning with endoscopic images is a pathway of great interest as described in section 1.7.7, with IPCLs as a potential target, based on previous studies of NBI for the diagnosis of GORD. CNNs involving IPCL detection and morphology have been recently reported in the context of a pilot study for the computer assisted diagnosis of oesophageal early squamous cell cancer using segmentation technology with accuracy matching expert endoscopists (Zhao et al., 2018). The image segmentation technique of Adaptive Local Thresholding has been demonstrated to be useful in vessel detection in retinal photographs making this as attractive technique for IPCLs (Jiang and Mojon, 2003).
- Conditions
- Gastro Esophageal Reflux
- Being tested
- wireless pH capsule recording
- Medical subject headings
- Gastroesophageal Reflux
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
wireless pH capsule recordingDiagnostic test
wireless pH capsule recording for up to 96 hours
| Study group | Role | What they receive |
|---|---|---|
| Gastro-Esophageal Reflux Disease | Patients defined as having GERD as per Lyon Consensus Receives: Diagnostic Test: wireless pH capsule recording | |
| Non-acid Reflux | Patient excluded for GERD as per Lyon Consensus Receives: Diagnostic Test: wireless pH capsule recording |
What is being measured
The primary outcome is the main question the study is designed to answer.
To evaluate Intra-Papillary Capillary Loop (IPCL) changes secondary to oesophageal acid exposure.
Parameters of IPCLs: IPCLs/region of interest, morphology: IPCL length, density correlated to oesophageal acid exposure
Measured: 6 weeks post completion of wireless capsule pH recording
To develop an accurate and reliable artificial intelligence model for the diagnosis of Gastro-Oesophageal Reflux Disease (GORD)
Patient data split into training/validation and test dataset for computer assisted and deep learning model training and testing
Measured: 3 months after completion of all data collection
Secondary outcomes (1)
To explore factors that may predict response to treatment.
Statistical analysis of models for IPCL number/ROI and morphology features against response to an antacid medication challenge.
Measured: 6 weeks to include data of response to antacid treatment
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Feb 2020
- Study start23 Nov 2017
- Primary completion26 Jul 2018
- Study completion30 Nov 2018
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (14)Papers the sponsor has linked to this study.
- Other trials for Gastro Esophageal RefluxStudies of the same condition, open and under way.
- More trials run by King's College Hospital NHS TrustThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 76 participants (actual)
Sponsor and investigators
- Lead sponsor
- King's College Hospital NHS Trust
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04268719
- Sponsor's protocol ID
- 227223
- Status last verified
- Feb 2020
- First submitted
- 11 Feb 2020
- Last updated
- 13 Feb 2020
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Protocol possible to obtain upon request
Publications
Vakil N, van Zanten SV, Kahrilas P, Dent J, Jones R; Global Consensus Group. The Montreal definition and classification of gastroesophageal reflux disease: a global evidence-based consensus. Am J Gastroenterol. 2006 Aug;101(8):1900-20; quiz 1943. doi: 10.1111/j.1572-0241.2006.00630.x.
PubMed 16928254Nikaki K, Woodland P, Sifrim D. Adult and paediatric GERD: diagnosis, phenotypes and avoidance of excess treatments. Nat Rev Gastroenterol Hepatol. 2016 Sep;13(9):529-42. doi: 10.1038/nrgastro.2016.109. Epub 2016 Jul 27.
PubMed 27485786Gyawali CP, Kahrilas PJ, Savarino E, Zerbib F, Mion F, Smout AJPM, Vaezi M, Sifrim D, Fox MR, Vela MF, Tutuian R, Tack J, Bredenoord AJ, Pandolfino J, Roman S. Modern diagnosis of GERD: the Lyon Consensus. Gut. 2018 Jul;67(7):1351-1362. doi: 10.1136/gutjnl-2017-314722. Epub 2018 Feb 3.
PubMed 29437910Lundell LR, Dent J, Bennett JR, Blum AL, Armstrong D, Galmiche JP, Johnson F, Hongo M, Richter JE, Spechler SJ, Tytgat GN, Wallin L. Endoscopic assessment of oesophagitis: clinical and functional correlates and further validation of the Los Angeles classification. Gut. 1999 Aug;45(2):172-80. doi: 10.1136/gut.45.2.172.
PubMed 10403727Nozu T, Komiyama H. Clinical characteristics of asymptomatic esophagitis. J Gastroenterol. 2008;43(1):27-31. doi: 10.1007/s00535-007-2120-2. Epub 2008 Feb 24.
PubMed 18297432Zagari RM, Fuccio L, Wallander MA, Johansson S, Fiocca R, Casanova S, Farahmand BY, Winchester CC, Roda E, Bazzoli F. Gastro-oesophageal reflux symptoms, oesophagitis and Barrett's oesophagus in the general population: the Loiano-Monghidoro study. Gut. 2008 Oct;57(10):1354-9. doi: 10.1136/gut.2007.145177. Epub 2008 Apr 18.
PubMed 18424568Lee YC, Lin JT, Chiu HM, Liao WC, Chen CC, Tu CH, Tai CM, Chiang TH, Chiu YH, Wu MS, Wang HP. Intraobserver and interobserver consistency for grading esophagitis with narrow-band imaging. Gastrointest Endosc. 2007 Aug;66(2):230-6. doi: 10.1016/j.gie.2006.10.056.
PubMed 17643694Fock KM, Teo EK, Ang TL, Tan JY, Law NM. The utility of narrow band imaging in improving the endoscopic diagnosis of gastroesophageal reflux disease. Clin Gastroenterol Hepatol. 2009 Jan;7(1):54-9. doi: 10.1016/j.cgh.2008.08.030. Epub 2008 Sep 3.
PubMed 18852068Inoue H, Kaga M, Ikeda H, Sato C, Sato H, Minami H, Santi EG, Hayee B, Eleftheriadis N. Magnification endoscopy in esophageal squamous cell carcinoma: a review of the intrapapillary capillary loop classification. Ann Gastroenterol. 2015 Jan-Mar;28(1):41-48.
PubMed 25608626Kato M, Kaise M, Yonezawa J, Toyoizumi H, Yoshimura N, Yoshida Y, Kawamura M, Tajiri H. Magnifying endoscopy with narrow-band imaging achieves superior accuracy in the differential diagnosis of superficial gastric lesions identified with white-light endoscopy: a prospective study. Gastrointest Endosc. 2010 Sep;72(3):523-9. doi: 10.1016/j.gie.2010.04.041. Epub 2010 Jul 3.
PubMed 20598685Sharma P, Wani S, Bansal A, Hall S, Puli S, Mathur S, Rastogi A. A feasibility trial of narrow band imaging endoscopy in patients with gastroesophageal reflux disease. Gastroenterology. 2007 Aug;133(2):454-64; quiz 674. doi: 10.1053/j.gastro.2007.06.006. Epub 2007 Jun 8.
PubMed 17681166Lv J, Liu D, Ma SY, Zhang J. Investigation of relationships among gastroesophageal reflux disease subtypes using narrow band imaging magnifying endoscopy. World J Gastroenterol. 2013 Dec 7;19(45):8391-7. doi: 10.3748/wjg.v19.i45.8391.
PubMed 24363532Pace F, Buscema M, Dominici P, Intraligi M, Baldi F, Cestari R, Passaretti S, Bianchi Porro G, Grossi E. Artificial neural networks are able to recognize gastro-oesophageal reflux disease patients solely on the basis of clinical data. Eur J Gastroenterol Hepatol. 2005 Jun;17(6):605-10. doi: 10.1097/00042737-200506000-00003.
PubMed 15879721Zhao YY, Xue DX, Wang YL, Zhang R, Sun B, Cai YP, Feng H, Cai Y, Xu JM. Computer-assisted diagnosis of early esophageal squamous cell carcinoma using narrow-band imaging magnifying endoscopy. Endoscopy. 2019 Apr;51(4):333-341. doi: 10.1055/a-0756-8754. Epub 2018 Nov 23.
PubMed 30469155
Study at a glance
From the registry record, last updated by the sponsor on 13 Feb 2020. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Near Focus NBI-Driven Artificial Intelligence for the Diagnosis of Gastro-Oesophageal Reflux Disease
- ClinicalTrials.gov ID
- NCT04268719
- Acronym / sponsor ID
- 227223
- Conditions
- Gastro Esophageal Reflux
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 76 participants (actual)
- Lead sponsor
- King's College Hospital NHS TrustUniversity, hospital or other
- Study start
- 23 Nov 2017 (actual)
- Primary completion
- 26 Jul 2018 (actual)
- Study completion
- 30 Nov 2018 (actual)
- First posted
- 13 Feb 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Gastro-oesophageal reflux disease (GORD) is a chronic condition with symptoms arising secondary to the reflux of stomach contents (Vakil et al., 2006). It is divided into four phenotypes: Erosive Oesophagitis (EO), Non-Erosive Reflux Disease (NERD), Reflux Hypersensitivity (RH), Functional Heartburn (FH) (Nikaki, Woodland and Sifrim, 2016). The definition of these phenotype have evolved with the addition of diagnostic tests and methods of their interpretation, the most recent being the Lyon Consensus Statement (Gyawali et al., 2018). The majority of patients presenting with symptoms suggestive of GORD have no mucosal lesion seen at endoscopy (Nikaki, Woodland and Sifrim, 2016). Studies have shown a relation of increased IPCL numbers with GORD. This study aims to build a fully autmoated AI model using Near-Focus NBI images on patients with symptoms suggestive of GORD phenotyped in accordance with the Lyon Consensus.
Detailed description
Gastro-oesophageal reflux disease (GORD) is a chronic condition with symptoms arising secondary to the reflux of stomach contents (Vakil et al., 2006). It is divided into four phenotypes: Erosive Oesophagitis (EO), Non-Erosive Reflux Disease (NERD), Reflux Hypersensitivity (RH), Functional Heartburn (FH) (Nikaki, Woodland and Sifrim, 2016). The definition of these phenotype have evolved with the addition of diagnostic tests and methods of their interpretation, the most recent being the Lyon Consensus Statement (Gyawali et al., 2018). The majority of patients presenting with symptoms suggestive of GORD have no mucosal lesion seen at endoscopy (Nikaki, Woodland and Sifrim, 2016). Complications of GORD, such as peptic stricture and Barrett's oesophagus, can be readily diagnosed using WLE. The diagnosis of reflux oesophagitis with standard-definition WLE is well described in the Los Angeles (LA) classification (Armstrong et al., 1996) and validated (Lundell et al., 1999) with LA grades C and D confirmatory of GORD (Gyawali et al., 2018). Furthermore, AET is demonstrated to increase with LA classification A to D (Lundell et al., 1999). There is, however, only a modest inter-observer agreement between LA grades (Kappa coefficient 0.4), especially A and B. Furthermore LA grade A oesophagitis is detected in up to 17.0% of asymptomatic patients (Nozu and Komiyama, 2008; Zagari et al., 2008). A diagnosis of GORD and decisions for anti-reflux surgery cannot be made on this basis, mandating pH testing to confirm GORD.
Narrow Band Imaging
Imaging of the gastro-oesophageal junction using high definition Olympus H260 scope using the LA classification of GORD with WLE and NBI demonstrated improvement in overall interobserver reproducibility when used in a combination compared with WLE alone; k 0.62 vs 0.45 (<0.05)(Lee et al., 2007). Features identified using digital magnification NBI at the squamo-columnar junction in cases of EO (n=41; LA grade A and B), NERD (n=36) and controls (n=32) include micro-erosions (100% EO; 52.8% NERD; 23.3% controls), increased vascularity (95.1% EO; 91.7% NERD; 36.7% controls) and round pit patterns (4.9% EO; 5.6% NERD; 70% controls). Increased vascularity combined with absence of round pit pattern distinguishes NERD from controls with sensitivity and specificity 86.1% and 83.3%. Inter-observer agreement in this single centre study was good for increased vascularity (k=0.95) and micro erosions (k=0.89) but low for pit pattern (k=0.59) (Fock et al., 2009).
Intra-papillary capillary loops (IPCLs) are mucosal capillaries arising from the submucosal vein to the papilla, usually arranged in a regular 'dot' like fashion approximately 100micrometres apart (Inoue, 2001). The visualisation of oesophageal IPCLs with NBI is well documented and form the basis of a NBI classification for squamous neoplasia (Inoue et al., 2015). IPCL morphology changes have been proposed in patients being investigated for NERD, in particular dilatation and elongation of IPCLs in patients with NERD with magnification NBI (Kato et al., 2006).
NBI with optical magnification for the diagnosis of GORD has been evaluated in 2 studies (Sharma et al., 2007; Lv et al., 2013). Sharma et al performed a feasibility trial with Olympus Q240Z with quadrantic examination of the distal 5cm by WLE then NBI in n=50 GORD (EO n=30; NERD n=20) and controls (n=30). Similar to Fock et al, the presence of microerosions and hypervascularity was significantly higher amongst GORD. IPCL number and morphology of tortuosity, dilatation were seen significantly more in GORD versus control. These findings were consistent in independent comparison of EO and NERD versus controls. ROC analysis thresholds for best sensitivity and specificity (respectively) for NERD were maximum ipcl/field 131 (90%, 70%), min 99 (85%, 70%) and average 117 (90%, 70%) (Sharma et al., 2007).
Lv et al used the Olympus GIF-H260Z to evaluate NERD (n=40), EO (n=40), Barrett's (n=40) and healthy controls (n=40). IPCL number, morphology (prolonged/dilated/tortuous), microerosions, round pit pattern above or below the SCJ, were recorded as features of reflux. Significant differences were found with increased IPCL number, microerosions, non-round pit patterns below the SCJ in GERD (NERD/EO and BE) patients compared to controls and fewer microerosions in NERD patients compared to RE (Lv et al., 2013).
The definition of NERD in all studies to date, however, is variable and largely based on symptom evaluation, response to PPI and the absence of mucosal lesions at endoscopic examination without standardisation using pH studies.
Artificial Intelligence
To date there is one study evaluating the use of ANNs in predicting GORD based on 45 variables including demographics, medical history, health status, symptoms scores. All patients underwent OGD, 24-pH studies performed in those with no mucosal lesion at endoscopy: 103 GORD patient (62 with reflux oesophagitis and 41 with AET>5%) and n=56 FH patients GORD. The ANN demonstrated an accuracy of 100% compared to 78% using conventional statistical regression analysis (Pace et al., 2005). While these are optimistic findings, the proportion of training and test data used was not specified and further evaluation with larger datasets is clearly warranted. There are no image-driven AI models for the diagnosis of GORD to date. Machine learning with endoscopic images is a pathway of great interest as described in section 1.7.7, with IPCLs as a potential target, based on previous studies of NBI for the diagnosis of GORD. CNNs involving IPCL detection and morphology have been recently reported in the context of a pilot study for the computer assisted diagnosis of oesophageal early squamous cell cancer using segmentation technology with accuracy matching expert endoscopists (Zhao et al., 2018). The image segmentation technique of Adaptive Local Thresholding has been demonstrated to be useful in vessel detection in retinal photographs making this as attractive technique for IPCLs (Jiang and Mojon, 2003).
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Gastro-Esophageal Reflux Disease | – | Diagnostic Test: wireless pH capsule recordingPatients defined as having GERD as per Lyon Consensus |
| Non-acid Reflux | – | Diagnostic Test: wireless pH capsule recordingPatient excluded for GERD as per Lyon Consensus |
Who may qualify
- Ages
- 18 to 90 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Consecutive patients attending the Gastroenterology department for the investigation of symptoms suggestive of Gastro-Oesophageal Reflux Disease (GORD) were approached for recruitment. Patients had to have symptoms including heartburn, regurgitation or chest/epigastric pain for a minimum of 3 months.
Key inclusion criteria (2 listed)
- Retaining capacity and medically fit for gastroscopy
- Requiring gastroscopy by current BSG guidelines for the investigation of acid reflux/ dyspepsia
Key exclusion criteria (6 listed)
- Unable to give informed consent
- History of oesophageal or gastric surgery
- Allergy to proton-pump inhibitor
- Known Barrett's Oesophagus/ oesophageal carcinoma/ oesophageal stricture/ known oesophageal dysmotility
- Portal Hypertension
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| wireless pH capsule recordingwireless pH capsule recording for up to 96 hours | Diagnostic test | Gastro-Esophageal Reflux Disease, Non-acid Reflux |
Primary outcome
To evaluate Intra-Papillary Capillary Loop (IPCL) changes secondary to oesophageal acid exposure.
Time frame: 6 weeks post completion of wireless capsule pH recording
Parameters of IPCLs: IPCLs/region of interest, morphology: IPCL length, density correlated to oesophageal acid exposure
To develop an accurate and reliable artificial intelligence model for the diagnosis of Gastro-Oesophageal Reflux Disease (GORD)
Time frame: 3 months after completion of all data collection
Patient data split into training/validation and test dataset for computer assisted and deep learning model training and testing
1 secondary outcome
To explore factors that may predict response to treatment.
Time frame: 6 weeks to include data of response to antacid treatment
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Feb 2020.
- Background: PubMed 16928254Vakil N, van Zanten SV, Kahrilas P, Dent J, Jones R; Global Consensus Group. The Montreal definition and classification of gastroesophageal reflux disease: a global evidence-based consensus. Am J Gastroenterol. 2006 Aug;101(8):1900-20; quiz 1943. doi: 10.1111/j.1572-0241.2006.00630.x.
- Background: PubMed 27485786Nikaki K, Woodland P, Sifrim D. Adult and paediatric GERD: diagnosis, phenotypes and avoidance of excess treatments. Nat Rev Gastroenterol Hepatol. 2016 Sep;13(9):529-42. doi: 10.1038/nrgastro.2016.109. Epub 2016 Jul 27.
- Background: PubMed 29437910Gyawali CP, Kahrilas PJ, Savarino E, Zerbib F, Mion F, Smout AJPM, Vaezi M, Sifrim D, Fox MR, Vela MF, Tutuian R, Tack J, Bredenoord AJ, Pandolfino J, Roman S. Modern diagnosis of GERD: the Lyon Consensus. Gut. 2018 Jul;67(7):1351-1362. doi: 10.1136/gutjnl-2017-314722. Epub 2018 Feb 3.
- Background: PubMed 10403727Lundell LR, Dent J, Bennett JR, Blum AL, Armstrong D, Galmiche JP, Johnson F, Hongo M, Richter JE, Spechler SJ, Tytgat GN, Wallin L. Endoscopic assessment of oesophagitis: clinical and functional correlates and further validation of the Los Angeles classification. Gut. 1999 Aug;45(2):172-80. doi: 10.1136/gut.45.2.172.
- Background: PubMed 18297432Nozu T, Komiyama H. Clinical characteristics of asymptomatic esophagitis. J Gastroenterol. 2008;43(1):27-31. doi: 10.1007/s00535-007-2120-2. Epub 2008 Feb 24.
- Background: PubMed 18424568Zagari RM, Fuccio L, Wallander MA, Johansson S, Fiocca R, Casanova S, Farahmand BY, Winchester CC, Roda E, Bazzoli F. Gastro-oesophageal reflux symptoms, oesophagitis and Barrett's oesophagus in the general population: the Loiano-Monghidoro study. Gut. 2008 Oct;57(10):1354-9. doi: 10.1136/gut.2007.145177. Epub 2008 Apr 18.
- Background: PubMed 17643694Lee YC, Lin JT, Chiu HM, Liao WC, Chen CC, Tu CH, Tai CM, Chiang TH, Chiu YH, Wu MS, Wang HP. Intraobserver and interobserver consistency for grading esophagitis with narrow-band imaging. Gastrointest Endosc. 2007 Aug;66(2):230-6. doi: 10.1016/j.gie.2006.10.056.
- Background: PubMed 18852068Fock KM, Teo EK, Ang TL, Tan JY, Law NM. The utility of narrow band imaging in improving the endoscopic diagnosis of gastroesophageal reflux disease. Clin Gastroenterol Hepatol. 2009 Jan;7(1):54-9. doi: 10.1016/j.cgh.2008.08.030. Epub 2008 Sep 3.
- Background: PubMed 25608626Inoue H, Kaga M, Ikeda H, Sato C, Sato H, Minami H, Santi EG, Hayee B, Eleftheriadis N. Magnification endoscopy in esophageal squamous cell carcinoma: a review of the intrapapillary capillary loop classification. Ann Gastroenterol. 2015 Jan-Mar;28(1):41-48.
- Background: PubMed 20598685Kato M, Kaise M, Yonezawa J, Toyoizumi H, Yoshimura N, Yoshida Y, Kawamura M, Tajiri H. Magnifying endoscopy with narrow-band imaging achieves superior accuracy in the differential diagnosis of superficial gastric lesions identified with white-light endoscopy: a prospective study. Gastrointest Endosc. 2010 Sep;72(3):523-9. doi: 10.1016/j.gie.2010.04.041. Epub 2010 Jul 3.
- Background: PubMed 17681166Sharma P, Wani S, Bansal A, Hall S, Puli S, Mathur S, Rastogi A. A feasibility trial of narrow band imaging endoscopy in patients with gastroesophageal reflux disease. Gastroenterology. 2007 Aug;133(2):454-64; quiz 674. doi: 10.1053/j.gastro.2007.06.006. Epub 2007 Jun 8.
- Background: PubMed 24363532Lv J, Liu D, Ma SY, Zhang J. Investigation of relationships among gastroesophageal reflux disease subtypes using narrow band imaging magnifying endoscopy. World J Gastroenterol. 2013 Dec 7;19(45):8391-7. doi: 10.3748/wjg.v19.i45.8391.
- Individual participant dataSharing planned: No. Protocol possible to obtain upon request
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Gastro Esophageal Reflux, run by King's College Hospital NHS Trust at 1 site in United Kingdom.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 13 Feb 2020. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United Kingdom. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
To evaluate Intra-Papillary Capillary Loop (IPCL) changes secondary to oesophageal acid exposure. (time frame: 6 weeks post completion of wireless capsule pH recording). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04268719, which also lists 14 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 13 Feb 2020.