Introduction

Dyspeptic patients frequently report nausea and vomiting. However, Rome IV criteria distinguish functional dyspepsia (FD) and chronic nausea and vomiting syndrome (CNVS) as separate disorders.

Aims & Methods

We aimed to assess and compare the characteristics and symptoms of patients with FD alone, with CNVS alone and those fulfilling both FD+CNVS criteria in a population of investigated dyspepsia. The retrospective study included 3,471 consecutive patients with investigated dyspepsia. Functional dyspepsia and CNVS were diagnosed according to Rome IV criteria. The severity of eight digestive symptoms during the 15 days preceding their appointment was assessed prospectively using a 5-point Likert scale. Quality of life (QoL) was quantified by the GastroIntestinal Quality of Life Index (GIQLI). Anxiety and depression were evaluated using the Hospital Anxiety and Depression scale (HADS). Sleep was assessed by the Pittsburgh Sleep Quality Index (PSQI).

Results

Among the 2,317 patients kept for analysis, 651 had FD alone, 144 CNVS alone and 393 FD+CNVS overlap. 73.2% of patients with CNVS fulfilled the criteria for FD, whereas 37.6% of FD patients met the criteria for CNVS. Patients with FD+CNVS overlap had worse quality of life, higher depression levels, and worse sleep quality than both diagnoses alone (p < 0.05). All symptoms were at least as prevalent in patients with FD+CNVS overlap as in patients with FD alone, except early satiation.

Conclusion

Nausea and vomiting are frequently reported by patients investigated for dyspepsia. Nearly three-quarters of patients with CNVS fulfil the criteria for FD, whereas more than one-third of FD patients meet the criteria for CNVS. Patients exhibiting FD+CNVS overlap have more severe disease than those with FD or CNVS alone.

Introduction

Colon Capsule Endoscopy (CCE) offers a non-invasive alternative to colonoscopy for lower gastrointestinal (GI) investigations. However, its adoption is limited by lengthy reading times, reader fatigue, and variable diagnostic accuracy. These factors are often influenced by bowel preparation quality and completion rates. Artificial intelligence (AI) has shown the potential to improve diagnostic accuracy of polyp detection and reduce reading times in capsule endoscopy.

Aims & Methods

Objective(s): The primary aim is to assess the diagnostic accuracy of Computer-Aided Detection (CADe) system (AiSPEED™) assisted CCE reading using full-video analysis in a real-world clinical setting. Secondary outcome was to assess a) non-inferiority compared to standard clinician reading in detecting polypoid lesions and b) mean reading time.
Methods: CESCAIL study is a multi-centre study of 14 UK centres recruited 720 participants between November 2021 and September 2024. Participants (prospectively and retrospectively enrolled ) included those ≥18 years referred for CCE under the urgent cancer pathway or for post-polypectomy surveillance. CCEs were performed using PillCam™ COLON 2 and analysed using AiSPEED™. CCE videos were evaluated by separate clinicians who provided standard readings, while AI-assisted reading included an AI-assisted pre-reader review and subsequent clinician validation.

Results

720 patients were enrolled, with 673 included in the final analysis. The capsule excretion rate before battery depletion was 77.1%, with adequate bowel preparation achieved at 78.1% (with standard) and 74.0% (with AI-assisted reading) (McNemar p=0.108). In the per-patient analysis, the diagnostic yield for detecting polyps was 63.6% (428/673) for standard reading and 70.6% (475/673) for AI-assisted reading, using the expert panel as the reference standard. These findings confirmed both non-inferiority (p<0.001) and superiority (p<0.001) of the AI-assisted reading. The diagnostic accuracy for detecting polyps requiring follow-up procedure (flexible sigmoidoscopy/colonoscopy) was 0.96 (95% CI: 0.95–0.98) for AI-assisted reading, compared to 0.91 (95% CI: 0.89–0.93) for standard reading (p<0.0001) (see Table 1). The mean reading time per video was 8.7 minutes for AI-assisted reading compared to 47.3 minutes for standard reading, representing a 5.4-fold reduction.

Conclusion

AI-assisted reading with AiSPEED™ offers the potential for greater accuracy in polyp detection and significantly reduced clinician reading times during CCE examination compared to standard reading methods.

References

1. Moen S, Vuik FER, Kuipers EJ, Spaander MCW. Artificial Intelligence in Colon Capsule Endoscopy-A Systematic Review. Diagnostics (Basel). 2022;12(8).
2. Mota J, Joao Almeida M, Mendes F, Martins M, Ribeiro T, Afonso J, et al. A Comprehensive Review of Artificial Intelligence and Colon Capsule Endoscopy: Opportunities and Challenges. Diagnostics (Basel). 2024;14(18).
3. Spada C, Piccirelli S, Hassan C, Ferrari C, Toth E, Gonzalez-Suarez B, et al. AI-assisted capsule endoscopy reading in suspected small bowel bleeding: a multicentre prospective study. Lancet Digit Health. 2024;6(5):e345-e53.
4. Spada C, Hassan C, Galmiche JP, Neuhaus H, Dumonceau JM, Adler S, et al. Colon capsule endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Guideline. Endoscopy. 2012;44(5):527-36.
5. PillCam COLON 2 for investigation of the colon through direct visualisation [Internet]. NATIONAL INSTITUTE FOR HEALTH AND CARE EXCELLENCE. August 2024. Available from: https://www.nice.org.uk/guidance/gid-dg10083/documents/final-scope-2.

Disclosure

Hagen Wenzek serves as the CEO, and Elizabeth White is the Project Manager at Corporate Health International which owns the ​intellectual property of AiSPEED^TM

Clinical Case Summary

Background: Acute liver failure (ALF) due to metastatic melanoma is rare and may mimic other hepatic pathologies, including Budd-Chiari syndrome. In the absence of cutaneous lesions, diagnosis can be delayed, complicating timely management.
Case Presentation: A 61-year-old male with a history of hypertension and dyslipidemia presented with a two-week history of abdominal pain, anorexia and jaundice. He had no prior liver disease or alcohol use. Laboratory workup revealed hyperbilirubinemia (90 µmol/L), coagulopathy (INR 1.72), and hepatocellular injury (ALT 500 IU/L, AST 800 IU/L). Viral hepatitis were excluded. Ultrasound maging demonstrated hepatomegaly, heterogeneous liver parenchyma and minimal ascites. The patient developed hepatic encephalopathy (GCS 11, West Haven grade 3) with hyperammonemia (300 µmol/L) and was transferred to a transplant center. MSCT revealed a massively enlarged liver (32x25x31 cm), fatty infiltration, right and middle hepatic vein compression, left hepatic vein thrombosis and intrahepatic IVC obliteration, suggesting Budd-Chiari syndrome syndrome and urgent pre-transplant workup. Rapid deterioration ensued with encephalopathy, renal failure (eGFR 30), worsening coagulopathy (INR 3.5), hyperbilirubinemia (190 µmol/L), lactic acidosis and hypoglycemia, requiring ICU care, intubation, vasopressors and dialysis. Percutaneous liver biopsy showed near-total hepatic replacement by necrotic spindle-shaped, HMB-45-positive pigmented tumor cells, confirming metastatic melanoma. Liver transplantation was contraindicated, and the patient died two days later. A uveal melanoma origin was suspected but unconfirmed due to lack of autopsy.
Conclusion: Metastatic melanoma can present without skin lesions and may mimic Budd-Chiari syndrome. Infiltrative malignancy should be considered in ALF of unclear etiology. Liver biopsy remains essential for diagnosis. Early multidisciplinary evaluation is critical to guide prognosis and avoid futile interventions.