Introduction: To investigate the potential clinical value of ambulatory monitoring of abdominal myoelectrical signals in the diagnostic investigation of GI functional disorders. Methods: Abdominal surface myoelectric data was acquired as per Part 1. Data from different subjects were normalized to one another. Peaks in the frequency spectrum were algorithmically identified and their total volume calculated. This was performed for the pre-prandial hour, a post-prandial 40-minute period, and the final hour. Data was processed to determine the rhythmic electrical activity levels of the stomach, small intestine, and colon. Peak volumes reflecting the level of rhythmic electrical activity were used to create a percentile ranking of each organ (stomach, small intestine, colon) for each test, as compared to all other tests in the study. In this measure, a rank of 50th percentile is average, less than 25th is considered low, and over 75th is high activity. Results: Patients had a variety of symptom combinations suggestive of diffuse dysmotility: 87% had bloating, 72% abdominal pain, 59% constipation, and 41% diarrhea. Controls did not report any GI symptoms for at least the previous 6 months. All recordings were well tolerated and there were no adverse events. Figures 1a - 1d show ranking values for 4 patients as bar graphs, with each bar representing an organ’s activity. Patients exhibited a wider distribution than controls (quadrature sum of deviation from mean overall organs of 0.900 ± 0.16 vs. 0.737 ± 0.14 respectively). For the tests with a single control subject, we found average reproducibility of 12% in percentile of each organ, and a very similar inter-organ pattern in 4 of 5 tests. For 3 repeated tests of patients, we also had good-to-excellent pattern reproducibility.Figure 1: Percentile activity rankings for 4 symptomatic patients. Short bars imply hypo-motility while long bars suggest hyper-motility. Figure 1c shows pan-GI dysmotility.Conclusion: A wireless patch system for monitoring myoelectric signals from the GI tract is feasible, reproducible and safe. Although the 3-hour recordings provide much more limited systematic and statistical power than will be the case with a multi-day test, these results provide new insights in GI motility disorders. Disclosure - Dr. Triadafilopoulos - Consultant: G-Tech, Dr. Shah - Consultant: G-Tech, Dr. Axelrod - Employee: G-Tech, Dr. Navalgund - Employee: G-Tech, Dr. Devanaboyina - Employee: G-Tech.
Rituximab is a monoclonal antibody commonly used to treat various autoimmune diseases.However, its use has been associated with the development of interstitial lung disease (ILD), a severe and potentially fatal condition characterized by inflammation and fibrosis of the lungs.This case report describes the case of a patient who developed ILD following treatment with rituximab for Diffuse large B cell lymphoma.The patient presented with symptoms of shortness of breath, dry cough, and fever, and was diagnosed with ILD following a comprehensive evaluation.The patient was treated with corticosteroids and other immunosuppressive medications, with a favorable response.This report highlights the importance of recognizing and managing rituximabinduced ILD and underscores the need for close monitoring of patients receiving this drug.
Introduction: To determine what signals from the GI tract can be detected noninvasively at the abdominal skin surface using ECG hardware, and to assess their potential clinical value in functional GI disorders. Methods: Electrodes from 3 ECG systems (Texas Instruments TMS320C5515) were attached to the abdominal surface of 8 healthy subjects in a 3 by 10 array, spaced approximately 2” apart (Figure 1A). Subjects were fed a 700 kCal meal 60 minutes into the 3-hour testing period. Data was digitized at a rate of 40 Hz and recorded to a computer disk drive. Post-processing included removal of large amplitude artifacts and high-pass filtering at 1 cycle/minute (cpm), followed by Fourier transformation to frequency space over selected time subintervals. Frequency peaks were identified and measured for amplitude, width, and duration algorithmically. All recordings were tolerated and there were no adverse events.Figure 1: (A) displays the electrode arrangement, (B) shows sample time series data in which rhythmic behavior is evident, and (C) and (D) show frequency space representations with clear peaks for stomach and colon in (C) and broadly distributed small intestine activity in (D).Results: Clear periodic signals indicative of rhythmic activity were seen at several frequencies from below 3 to over 20 cpm (Figure 1B-D). Very sharp peaks around 3 cpm are known to be associated with the stomach. Immediately post-meal, there is a drop in frequency for many subjects, followed by a gradual return to fasting values, with occasional overshoot observed. Persistent small intestine peaks were routinely identified at 5-12 cpm. We also observed shorter bursts of activity at 16-18 cpm lasting for 10-20 minutes, which we associated with colonic activity. In some cases the “colonic” frequencies are as low as 13-14 cpm and as high as 20-24 cpm. The actual frequencies observed were consistent for each subject during a test and reproduced in repeat tests. Conclusion: The noninvasive measurement and algorithmic identification of signals at the skin surface representing rhythmic contractions of the stomach, small intestine, and colon using COTS ECG hardware is safe, feasible, and reproducible. The potential of ambulatory recordings for the diagnosis and management of patients with functional GI disorders will require further study. Disclosure - Dr. Triadafilopoulos - Consultant: G-Tech, Dr. Shah - Consultant: G-Tech, Dr. Axelrod - Employee: G-Tech, Dr. Navalgund - Employee: G-Tech, Dr. Devanaboyina - Employee: G-Tech.
Introduction: To examine the clinical value of myoelectrical signals detected at the abdominal skin surface in the diagnosis of functional GI disorders. Methods: Abdominal surface myoelectric data was acquired as per Part 1. Data from different subjects were normalized to one another. Peaks in the frequency spectrum were algorithmically identified and their total volume calculated. This was performed for the pre-prandial hour, a post-prandial 40-minute period, and the final hour. Results: Peak intensity was ranked as a percentile value for each organ against all subjects in the test. Figure 1A shows a frequency-space waterfall plot where peak activity can be seen at several frequencies at different times, including from the stomach near 3 cpm, commencing right after the meal, and colonic, from 16-20 cpm, near the end. Figure 1B shows a sample percentile rank bar graph for a control subject, where the ranks are near the 50th percentile and thus close to average. To establish reproducibility, 1 subject was tested 5 times under nominally identical conditions over a 7-month period (Figure 2). Between the 4th and 5th tests, the subject lost 15 lb. Reproducibility is very good for stomach and colon and fairly good for small intestine. Excluding the 5th test, the standard deviations are 4%, 16%, and 7%.Figure 1: (A) is a frequency-space waterfall plot showing peak activity at several frequencies occurring at various times. (B) shows a sample percentile rank bar graph for the same control subject.Figure 2: Reproducibility test on Control subject 103. Five tests were carried out over a 7-month period. Between the fourth and fifth tests, the subject lost 15 lbs.Conclusion: Algorithms developed to extract data from rhythmic peaks in the frequency spectrum of myoelectric recordings were used to determine the electrical activity level of the stomach, small intestine, and colon, in a model which assigns the activity to a given organ based on frequency. Such system provides a measure of smooth muscular activity of each organ that can be then used to gain insights into GI motility disorders. Disclosure - Dr. Triadafilopoulos - Consultant: G-Tech, Dr. Shah - Consultant: G-Tech, Dr. Axelrod - Employee: G-Tech, Dr. Navalgund - Employee: G-Tech, Dr. Devanaboyina - Employee: G-Tech.
'%3e%3ccircle r='20' fill='%23008'/%3e%3ccircle r='17.5' fill='%23fff'/%3e%3ccircle r='3.5' fill='%23008'/%3e%3cg id='d'%3e%3cg id='c'%3e%3cg id='b'%3e%3cg id='a' fill='%23008'%3e%3ccircle r='.875' transform='rotate(7.5 -8.75 133.5)'/%3e%3cpath d='M0 17.5.6 7 0 2l-.6 5L0 17.5z'/%3e%3c/g%3e%3cuse xlink:href='%23a' transform='rotate(15)'/%3e%3c/g%3e%3cuse xlink:href='%23b' transform='rotate(30)'/%3e%3c/g%3e%3cuse xlink:href='%23c' transform='rotate(60)'/%3e%3c/g%3e%3cuse xlink:href='%23d' transform='rotate(120)'/%3e%3cuse xlink:href='%23d' transform='rotate(-120)'/%3e%3c/g%3e%3c/svg%3e)
