Citations

SummaryBackgroundPredictive models for eosinophilic oesophagitis (EoE) may not fully rule in the diagnosis.AimTo develop a reverse model that predicts against EoE to eliminate the need for oesophageal biopsies.MethodsIn this two‐centre study, a predictive model was developed (Mayo Clinic) and validated (University of North Carolina [UNC]). Cross‐sectional data from consecutive adult patients without prior EoE who underwent upper enoscopy with oesophageal biopsies were used. EoE cases had ≥15 eosinophils/high‐power field while controls had no eosinophils. Data were collected on patient clinical and endoscopic features. Multiple variable logistic regression was used to identify predictors of non‐EoE status while maintaining specificity ≥95%. A secondary model was developed to predict against the need for endoscopy in patients suspected of having EoE without alarm symptoms.ResultsThe Mayo and UNC cohorts consisted of 345 (EoE = 94, non‐EoE = 251) and 297 patients (EoE = 84, non‐EoE = 213), respectively. A primary model based on clinical and endoscopic features predicted against EoE with c‐statistic 0.92 (95% CI: 0.88–0.96), specificity 95%, and sensitivity 65%. This model was validated (UNC) with c‐statistic 0.87 (95% CI: 0.82–0.92). A simplified scoring system was created and a threshold of ≥12 points excluded EoE with 95% specificity and 50% sensitivity. A secondary model based on clinical characteristics alone predicted against EoE with c‐statistic 0.86 (95% CI: 0.82–0.90), specificity 95% and sensitivity 39% and validated (UNC) with c‐statistic 0.78 (95% CI: 0.71–0.85).ConclusionA simplified scoring system accurately identified a group of patients with a low likelihood of EoE where unnecessary oesophageal biopsies can be avoided, potentially resulting in resource and cost savings.

INTRODUCTION: Endoscopic eradication therapy (EET) is standard of care for T1a esophageal adenocarcinoma (EAC). However, data on outcomes in high-risk T1a EAC are limited. We assessed and compared outcomes after EET of low-risk and high-risk T1a EAC, including intraluminal EAC recurrence, extraesophageal metastases, and overall survival. METHODS: Patients who underwent EET for T1a EAC at 3 referral Barrett's esophagus endotherapy units between 1996 and 2022 were included. Patients with submucosal invasion, positive deep margins, or metastases at initial diagnosis were excluded. High-risk T1a EAC was defined as T1a EAC with poor differentiation and/or lymphovascular invasion, with low-risk disease being defined without these features. All pathology was systematically assessed by expert gastrointestinal pathologists. Baseline and follow-up endoscopy and pathology data were abstracted. Time-to-event analyses were performed to compare outcomes between groups. RESULTS: One hundred eighty-eight patients with T1a EAC were included (high risk, n = 45; low risk, n = 143) with a median age of 70 years, and 84% were men. Groups were comparable for age, sex, Barrett's esophagus length, lesion size, and EET technique. Rates of delayed extraesophageal metastases (11.1% vs 1.4%) were significantly higher in the high-risk group ( P = 0.02). There was no significant difference in the rates of intraluminal EAC recurrence ( P = 0.79) and overall survival ( P = 0.73) between the 2 groups. DISCUSSION: Patients with high-risk T1a EAC undergoing successful EET had a substantially higher rate of extraesophageal metastases compared with those with low-risk T1a EAC on long-term follow-up. These data should be factored into discussions with patients while selecting treatment approaches. Additional prospective data in this area are critical.

SummaryBackgroundMedication use has been implicated in the development of microscopic colitis (MC). However, studies have demonstrated inconsistent findings and there exist variations in design.AimTo measure the association between medication use and MC.MethodsPatients who underwent a colonoscopy over a 10‐year period at two academic medical centres (Columbia University Medical Centre and Mayo Clinic) were identified. Cases were patients with biopsy‐proven MC and controls were patients who underwent colonoscopy for evaluation of diarrhoea with biopsies negative for MC. Cases were matched by age, gender and calendar period with up to two controls. Demographics, medication use, smoking history and coeliac disease status were collected. Conditional logistic regression was used with and without adjustment for smoking.ResultsA total of 344 patients with MC were matched to 668 controls. After adjusting for smoking, there was an inverse association between MC and use of proton pump inhibitors (PPIs) (OR 0.64; 95% CI 0.47‐0.87), H2 blockers (OR 0.46; 95% CI 0.24‐0.88) and oral diabetes medications (OR 0.47; 95% CI 0.27‐0.81). There was a positive association with nonsteroidal anti‐inflammatory drug (NSAID) use and MC (OR 1.63; 95% CI 1.12‐2.38).ConclusionsNSAID use was associated with MC, while use of PPIs, H2 blockers and oral diabetes medications were inversely related to MC. Our use of a control group with diarrhoea, as opposed to healthy controls, may have contributed to these inverse associations. Future studies of drug‐induced microscopic colitis should include control groups with diarrhoea, and not only healthy controls.

Background: Microscopic colitis (MC) causes chronic diarrhea. It has two histologic subtypes: lymphocytic colitis (LC) and collagenous colitis (CC). Little is known about the natural progression of disease with time and with treatment. Objectives: We aimed to assess histological changes over time. Design: We designed a retrospective study including adults diagnosed with MC from January 1992 to January 2020 at Mayo Clinic. Methods: Pathology reports were reviewed until 31 October 2020. Histological assessments at least 8 weeks apart were considered as adequate follow-up. Histological change from one subtype to the other and resolution were tracked with univariate and multivariable Cox proportional hazards models. Results: Overall, 416 patients with a median age at diagnosis of 63.9 years with >1 histopathological assessment were identified. Histology at initial diagnosis was CC in 218 (52.4%) patients and LC in 198 (47.6%). No medications were associated with a histological change. However, histological resolution was more likely with the use of aspirin [hazard ratio (HR): 2.10, 95% confidence interval (CI): 1.34–3.31, p = 0.001) and proton-pump inhibitors (PPIs; HR: 2.01, 95% CI: 1.34–3.02, p = 0.001). Histological resolution was more likely with budesonide treatment (HR: 1.86, 95% CI: 1.16–3.00, p = 0.010) and less likely with mesalamine (HR: 0.40, 95% CI: 0.19–0.83, p = 0.014), compared to medications such as prednisone, loperamide, and bismuth. Patients with CC were less likely to change their histology compared to patients with LC (HR: 0.24, 95% CI: 0.14–0.42, p < 0.001). There was no difference in histological resolution between the two subtypes (HR: 0.70, 95% CI: 0.47–1.05, p = 0.084). Conclusion: Patients with LC have a higher chance of changing their histology as compared to CC. However, histological resolution was associated with the use of PPIs and aspirin, and treatment with budesonide.

Pietrowicz et al. (2022) demonstrated feasibility of detecting potential speech-based biomarkers to identify gastroesophageal reflux disease (GERD) and Barrett’s esophagus (BE); however, speech samples were obtained using research-grade recording equipment (TASCAM DR-40X with AKG C555L microphone). The use of more readily available equipment such as the Apple iPad with a native microphone could simplify data collection and allow access to a broader range of participants. Therefore, this study compared the research-grade recordings to iPad recordings for feasibility of detecting GERD and BE. One-hundred-fifty adults, clinically classified as GERD negative or GERD positive with or without BE, recorded a paragraph (The Rainbow Passage) simultaneously on both a TASCAM and iPad. Both data sets were analyzed manually for Alpha Ratio and Cepstral Peak Prominence (CPP) with Praat. Initial results show significantly higher alpha ratio and lower CPP in iPad recordings, indicating greater noise energy in the high-frequency range. Additionally, the capability of machine and deep learning model types to discern across GERD negative, GERD positive, BE, and normal voices were compared. Detection across these conditions and comparison of acoustic findings were explored to determine usefulness of the less controlled option of recording using an iPad with its internal microphone.

This study explores the feasibility of detecting gastroesophageal reflux disease (GERD) and Barrett’s esophagus (BE) using acoustic features extracted from speech recordings. GERD is a common condition affecting up to 27.8% of adults in the US. Chronic GERD is associated with BE, the precursor to esophageal adenocarcinoma. An automatic screening tool for GERD would improve clinical outcomes by improving early detection. Biomarkers based on acoustic features of speech may hold promise as hoarseness often co-occurs with GERD. The study cohort consisted of 49 adults with and 63 without GERD based on esophagogastroduodenoscopy or ambulatory pH studies. Speech, including sustained vowels, sentences, and reading, was systematically recorded. Voice quality was validated through auditory-perceptualratings with three speech-language pathologists. Automated, cross-validated, search across multiple machine and deep learning model types was performed using the recorded speech. Detection of condition presence and severity are explored, and model performance is reported, along with an assessment of the ability of acoustic features to discern across conditions.