Introduction

The proportion of patients who take opioid based analgesics and cannabis has not been studied in a large cohort of patients with cyclical vomiting syndrome (CVS) in the UK. It is also unclear whether the efficacy of prophylactic tricyclic antidepressants (TCAs) is impacted by ongoing opioid or cannabis use.

Aims & Methods

(A) To study the burden of opioid and cannabis use in patients with CVS.
(B) To study the clinical response to prophylactic TCA and whether this was augmented by opioid/cannabis intake.
Clinical characteristics and healthcare outcomes of patients diagnosed with ROME IV CVS in a single neurogastroenterology clinic between January 2016 to December 2023 were retrospectively collected. A standardised clinic template was used to collect data relating to age, sex, gastrointestinal symptoms, medication usage, and patient-reported response to TCA. Patients commenced 10mg TCA for 60 days which was up titrated by 10 mg at each routine outpatient consultation (unless poorly tolerated) until clinical remission was achieved or the maxmum dose (50 mg daily) was prescribed. Clinical remission was defined as the absence of stereotypical episodes of vomiting for at least 6 months prior to the last clinic consultation.

Results

95 patients (male 21%, mean age 30.8±11.8 years) were identified and 84 (88%) were seen on at least two or more occasions with a median duration of follow-up of 22 (IQR: 5, 39) months. The treatment outcomes for all patients treated with TCA are outlined in table 1. At the initial consultation, 35 (37%) and 16 (17%) patients took prescribed opioid analgesics and cannabis, respectively. All were provided with drug cessation advice and were prescribed a TCA: only 12/35 (34%) and 11/16 (69%) of patients adhered to drug cessation advice. On follow-up, 100% of patients who adhered to recommendations to stop opioids and cannabis responded to TCA whilst 0% of patients who continued to take opioids/cannabis responded to TCA. Illicit drugs were found at urine drug screening in 5 patients who failed to respond to TCA (cocaine n=2 and heroin n=3).

Conclusion

This is the first UK study reporting the impact of opioid usage and illicit drugs in patients with CVS. TCAs are useful in treating CVS patients providing they do not consume prescribed opioids or illicit drugs.

Introduction

Anorectal disorders, causing fecal incontinence or evacuation dysfunction are common, affecting up to 5% of the general population (1). Most of these disorders result from an intricate combination of disturbances, including neurologic and pelvic floor musculature dysfunction, and have a significant impact in the quality of life of patients (2,3). Anorectal manometry (ARM) is the gold standard for the evaluation of anorectal functional disorders. Nevertheless, the accessibility to this exam is limited, and the complexity of data analysis and report is a significant drawback (4).

Aims & Methods

This pilot study aimed to develop and validate an artificial intelligence (AI) model to automatically differentiate motility patterns of fecal incontinence (FI) from obstructed defecation (OD) using ARM data.
We included ARM exams performed at a large gastrointestinal motility clinic in Brazil (Pelvia – Gastrointestinal Motility and Continence, Paraná, Brazil) between 2015 and 2021. All ARM procedures were performed using water-perfused probes with eight radial transducers with a distal latex balloon. We developed and tested multiple machine learning algorithms for the automatic interpretation of ARM data. Four models were tested: k-nearest neighbors (KNN), support vector machines (SVM), random forests (RF) and gradient boosting (xGB). These models were trained using a stratified 5-fold strategy. Their performance was assessed after fine-tuning of each model’s hyperparameters, using 90% of data for training and 10% of data for testing.

Results

A total of 827 ARM exams were used in this study, 493 of patients diagnosed with obstructed defecation (OD), while the remaining 334 presented FI. The performance marks of the different tuned models, including the precision, sensitivity and the F1-score, is summarized on table 1. After fine-tuning, the xGB model presented an overall accuracy (84.6 ± 2.9%), similar to that of RF (82.7 ± 4.8%) and SVM (81.0 ± 8.0%), and higher that of KNN (74.4 ± 3.8%). The xGB models showed the highest discriminating performance between OD and FI, with an area under the curve of 0.939.

Conclusion

The tested machine learning algorithms, particularly the xGB model, accurately differentiated between FI and OD manometric patterns. Subsequent development of these tools may optimize the access to ARM studies, which may significantly impact on the management of patients with anorectal functional diseases.

References

1. Whitehead WE, Wald A, Diamant NE, et al. Functional disorders of the anus and rectum. Gut 1999;45 Suppl 2:Ii55-9.
2. Maeda Y, Vaizey CJ, Hollington P, et al. Physiological, psychological and behavioural characteristics of men and women with faecal incontinence. Colorectal Dis 2009;11:927-32.
3. Remes-Troche JM, Rao SS. Defecation disorders: neuromuscular aspects and treatment. Curr Gastroenterol Rep 2006;8:291-9.
4. Brown HW, Guan W, Schmuhl NB, et al. If We Don't Ask, They Won't Tell: Screening for Urinary and Fecal Incontinence by Primary Care Providers. J Am Board Fam Med 2018;31:774-782.

Introduction

Contrast-enhanced harmonic endoscopic ultrasound (CEH-EUS) can demonstrate microvascularization of the tumors. However, most images acquired from CEH-EUS are interpreted subjectively without quantification by time-intensity curves (TICs) analysis. The role of quantitative CEH-EUS through time-intensity curve (TIC) has not been explored in differential diagnosis of gallbladder(GB) polypoid lesions.

Aims & Methods

Aim: In this study, we used a handcrafted software to quantify TIC curve of CEH-EUS images to differentiate malignant gallbladder polypoid lesions from benign ones.
Method: We analyzed the videos of CEH-EUS for GB polypoid lesions from the patients in National Taiwan University Hospital. The convex-type echoendoscope (GF-UCT260; Olympus, Tokyo, Japan) equipped with ultrasound (US) systems (EU-ME2) was used for the procedures. The second generation of US contrast agent with Sonazoid (GE Healthcare, Oslo, Norway), which contains perfluorobutane microbubbles with a median diameter of 2–3 μm, was administered bolus and intravenously with a dosage of 0.015 ml encapsulated gas per kilogram body weight. The videos were recorded in AVI formats with 30 frames/second.
The algorithm for getting TICs includes the following steps:
(1) Circling the region of interest(ROI) in the B-mode
(2) Performing speckle tracking of the ROI in the B-mode
(3) Simultaneously obtaining the intensity of ROI (the mean pixel values in the ROI) in the corresponding contrast-enhanced harmonic image
(4) Outputting TICs after subtracting the baseline intensity (for eliminating the different baseline intensities caused by other settings).
(5) Outputting histogram of pixel values and excel file containing all pixel values from the frame with the highest mean pixel value automatically.
(6) Calculating the standard variance of (5) to represent the heterogeneity inside the ROI.
The speckling tracking composes of searching and matching processes. We used full search for the searching process and normalization cross-correlation for the matching process. By using the hardware of CPU with Intel i7-8750H and GPU with Nvidia GTX 1050 Ti, the computation time was 0.7 ms/frame. Based on this algorithm, we designed a graphical user interface of this model.

Results

A total of 30 eligible videos were enrolled for analysis. Fourteen lesions were pathologically proven of malignancies (including 11 adenocarcinomas, two neuroendocrine tumors, one B-cell lymphoma) and the other 16 lesions were benign cases. Among 16 benign lesions, 6 were chronic cholecystitis, 4 were adenomyoma, 2 were intracholecystic papillary neoplasm, one was xanthogranulomatous cholecystitis, one was cholesterol polyps, one was hyperplastic polyp and one was Mycobacterium tuberculosis. The lesion size ranged from 8.1 to 90mm in malignant group and from 4.4 to 29mm in benign group. The mean peak intensity was 46.36 dB (SD=31.77) in malignant group and 55.94 dB (SD=44.59) in benign group respectively (p=.509). The mean time to peak was 30.14 s (SD=10.00) in malignant group and 20.50 s (SD=6.70) in benign group respectively (p=.004).

Conclusion

This preliminary report of using TIC of CEH-EUS images for differential diagnosis of GB polypoid lesions showed significant difference in time to peak between malignant group and benign group. Further large scale of studies are needed for comfirming the application of this novel technique.

Disclosure

Conflict of Interest