Gastric Alimetry Expands Patient Phenotyping in Gastroduodenal Disorders Compared with Gastric Emptying Scintigraphy.

INTRODUCTION: Gastric emptying testing (GET) assesses gastric motility, however, is nonspecific and insensitive for neuromuscular disorders. Gastric Alimetry (GA) is a new medical device combining noninvasive gastric electrophysiological mapping and validated symptom profiling. This study assessed patient-specific phenotyping using GA compared with GET. METHODS: Patients with chronic gastroduodenal symptoms underwent simultaneous GET and GA, comprising a 30-minute baseline, 99m TC-labelled egg meal, and 4-hour postprandial recording. Results were referenced to normative ranges. Symptoms were profiled in the validated GA App and phenotyped using rule-based criteria based on their relationships to the meal and gastric activity: (i) sensorimotor, (ii) continuous, and (iii) other. RESULTS: Seventy-five patients were assessed, 77% female. Motility abnormality detection rates were as follows: GET 22.7% (14 delayed, 3 rapid), GA spectral analysis 33.3% (14 low rhythm stability/low amplitude, 5 high amplitude, and 6 abnormal frequency), and combined yield 42.7%. In patients with normal spectral analysis, GA symptom phenotypes included sensorimotor 17% (where symptoms strongly paired with gastric amplitude, median r = 0.61), continuous 30%, and other 53%. GA phenotypes showed superior correlations with Gastroparesis Cardinal Symptom Index, Patient Assessment of Upper Gastrointestinal Symptom Severity Index, and anxiety scales, whereas Rome IV Criteria did not correlate with psychometric scores ( P > 0.05). Delayed emptying was not predictive of specific GA phenotypes. DISCUSSION: GA improves patient phenotyping in chronic gastroduodenal disorders in the presence and absence of motility abnormalities with increased correlation with symptoms and psychometrics compared with gastric emptying status and Rome IV criteria. These findings have implications for the diagnostic profiling and personalized management of gastroduodenal disorders.

Normative Values for Body Surface Gastric Mapping Evaluations of Gastric Motility Using Gastric Alimetry: Spectral Analysis.

INTRODUCTION: Body surface gastric mapping (BSGM) is a new noninvasive test of gastric function. BSGM offers several novel and improved biomarkers of gastric function capable of differentiating patients with overlapping symptom profiles. The aim of this study was to define normative reference intervals for BSGM spectral metrics in a population of healthy controls. METHODS: BSGM was performed in healthy controls using Gastric Alimetry (Alimetry, New Zealand) comprising a stretchable high-resolution array (8 × 8 electrodes; 196 cm 2 ), wearable Reader, and validated symptom-logging App. The evaluation encompassed a fasting baseline (30 minutes), 482 kCal meal, and 4-hour postprandial recording. Normative reference intervals were calculated for BSGM metrics including the Principal Gastric Frequency, Gastric Alimetry Rhythm Index (a measure of the concentration of power in the gastric frequency band over time), body mass index (BMI)-adjusted amplitude (µV), and fed:fasted amplitude ratio. Data were reported as median and reference interval (5th and/or 95th percentiles). RESULTS: A total of 110 subjects (55% female, median age 32 years [interquartile range 24-50], median BMI 23.8 kg/m 2 [interquartile range 21.4-26.9]) were included. The median Principal Gastric Frequency was 3.04 cycles per minute; reference interval: 2.65-3.35 cycles per minute. The median Gastric Alimetry Rhythm Index was 0.50; reference interval: ≥0.25. The median BMI-adjusted amplitude was 37.6 µV; reference interval: 20-70 µV. The median fed:fasted amplitude ratio was 1.85; reference interval ≥1.08. A higher BMI was associated with a shorter meal-response duration ( P = 0.014). DISCUSSION: This study provides normative reference intervals for BSGM spectral data to inform diagnostic interpretations of abnormal gastric function.

In Situ Pulmonary Arterial Thrombosis: Literature Review and Clinical Significance of a Distinct Entity.

Filling defects identified in the pulmonary arterial tree are commonly presumed to represent an embolic phenomenon originating from thrombi formed in remote veins, particularly lower-extremity deep venous thrombosis (DVT). However, accumulating evidence supports an underappreciated cause for pulmonary arterial thrombosis (PAT), namely, de novo thrombogenesis-whereby thrombosis arises within the pulmonary arteries in the absence of DVT. Although historically underrecognized, in situ PAT has become of heightened importance with the emergence of SARS-CoV-2 infection. In situ PAT is attributed to endothelial dysfunction, systemic inflammation, and acute lung injury and has been described in a range of conditions including COVID-19, trauma, acute chest syndrome in sickle cell disease, pulmonary infections, and severe pulmonary arterial hypertension. The distinction between pulmonary embolism and in situ PAT may have important implications regarding management decisions and clinical outcomes. In this review, we summarize the pathophysiology, imaging appearances, and management of in situ PAT in various clinical situations. This understanding will promote optimal tailored treatment strategies for this increasingly recognized entity.

Validation of noninvasive body-surface gastric mapping for detecting gastric slow-wave spatiotemporal features by simultaneous serosal mapping in porcine.

Gastric disorders are increasingly prevalent, but reliable noninvasive tools to objectively assess gastric function are lacking. Body-surface gastric mapping (BSGM) is a noninvasive method for the detection of gastric electrophysiological features, which are correlated with symptoms in patients with gastroparesis and functional dyspepsia. Previous studies have validated the relationship between serosal and cutaneous recordings from limited number of channels. This study aimed to comprehensively evaluate the basis of BSGM from 64 cutaneous channels and reliably identify spatial biomarkers associated with slow-wave dysrhythmias. High-resolution electrode arrays were placed to simultaneously capture slow waves from the gastric serosa (32 × 6 electrodes at 4 mm spacing) and epigastrium (8 × 8 electrodes at 20 mm spacing) in 14 porcine subjects. BSGM signals were processed based on a combination of wavelet and phase information analyses. A total of 1,185 individual cycles of slow waves were assessed, out of which 897 (76%) were classified as normal antegrade waves, occurring in 10 (71%) subjects studied. BSGM accurately detected the underlying slow wave in terms of frequency (r = 0.99, P = 0.43) as well as the direction of propagation (P = 0.41, F-measure: 0.92). In addition, the cycle-by-cycle match between BSGM and transitions of gastric slow wave dysrhythmias was demonstrated. These results validate BSGM as a suitable method for noninvasively and accurately detecting gastric slow-wave spatiotemporal profiles from the body surface.NEW & NOTEWORTHY Gastric dysfunctions are associated with abnormalities in the gastric bioelectrical slow waves. Noninvasive detection of gastric slow waves from the body surface can be achieved through multichannel, high-resolution, body-surface gastric mapping (BSGM). BSGM matched the spatiotemporal characteristics of gastric slow waves recorded directly and simultaneously from the serosal surface of the stomach. Abnormal gastric slow waves, such as retrograde propagation, ectopic pacemaker, and colliding wavefronts can be detected by changes in the phase of BSGM.

Mandating Limits on Workload, Duty, and Speed in Radiology.

Research has not yet quantified the effects of workload or duty hours on the accuracy of radiologists. With the exception of a brief reduction in imaging studies during the 2020 peak of the COVID-19 pandemic, the workload of radiologists in the United States has seen relentless growth in recent years. One concern is that this increased demand could lead to reduced accuracy. Behavioral studies in species ranging from insects to humans have shown that decision speed is inversely correlated to decision accuracy. A potential solution is to institute workload and duty limits to optimize radiologist performance and patient safety. The concern, however, is that any prescribed mandated limits would be arbitrary and thus no more advantageous than allowing radiologists to self-regulate. Specific studies have been proposed to determine whether limits reduce error, and if so, to provide a principled basis for such limits. This could determine the precise susceptibility of individual radiologists to medical error as a function of speed during image viewing, the maximum number of studies that could be read during a work shift, and the appropriate shift duration as a function of time of day. Before principled recommendations for restrictions are made, however, it is important to understand how radiologists function both optimally and at the margins of adequate performance. This study examines the relationship between interpretation speed and error rates in radiology, the potential influence of artificial intelligence on reading speed and error rates, and the possible outcomes of imposed limits on both caseload and duty hours. This review concludes that the scientific evidence needed to make meaningful rules is lacking and notes that regulating workloads without scientific principles can be more harmful than not regulating at all.

Narrowing the Gap: Imaging Disparities in Radiology.

It may seem unlikely that the field of radiology perpetuates disparities in health care, as most radiologists never interact directly with patients, and racial bias is not an obvious factor when interpreting images. However, a closer look reveals that imaging plays an important role in the propagation of disparities. For example, many advanced and resource-intensive imaging modalities, such as MRI and PET/CT, are generally less available in the hospitals frequented by people of color, and when they are available, access is impeded due to longer travel and wait times. Furthermore, their images may be of lower quality, and their interpretations may be more error prone. The aggregate effect of these imaging acquisition and interpretation disparities in conjunction with social factors is insufficiently recognized as part of the wide variation in disease outcomes seen between races in America. Understanding the nature of disparities in radiology is important to effectively deploy the resources and expertise necessary to mitigate disparities through diversity and inclusion efforts, research, and advocacy. In this article, the authors discuss disparities in access to imaging, examine their causes, and propose solutions aimed at addressing these disparities.

What do radiologists look for? Advances and limitations of perceptual learning in radiologic search.

Supported by guidance from training during residency programs, radiologists learn clinically relevant visual features by viewing thousands of medical images. Yet the precise visual features that expert radiologists use in their clinical practice remain unknown. Identifying such features would allow the development of perceptual learning training methods targeted to the optimization of radiology training and the reduction of medical error. Here we review attempts to bridge current gaps in understanding with a focus on computational saliency models that characterize and predict gaze behavior in radiologists. There have been great strides toward the accurate prediction of relevant medical information within images, thereby facilitating the development of novel computer-aided detection and diagnostic tools. In some cases, computational models have achieved equivalent sensitivity to that of radiologists, suggesting that we may be close to identifying the underlying visual representations that radiologists use. However, because the relevant bottom-up features vary across task context and imaging modalities, it will also be necessary to identify relevant top-down factors before perceptual expertise in radiology can be fully understood. Progress along these dimensions will improve the tools available for educating new generations of radiologists, and aid in the detection of medically relevant information, ultimately improving patient health.

Coronary balloon catheter tip damage. A bench study of a clinical problem.

OBJECTIVES: To confirm clinically that coronary balloon catheter tips may be damaged during bifurcation treatment with side-branch access through the side of a stent. On the bench, we aimed to assess the susceptibility of different balloon designs to damage. We compared catheter tip widths. We tested whether balloon tip flaring can cause stent distortion. BACKGROUND: We had observed that balloon catheters that failed to cross to a side-branch frequently exhibited tip damage. METHODS AND RESULTS: We examined microscopically for damage 82 balloon tips after clinical side-branch access. In a bench study, the forces required to compress catheter tips 0.5 mm were compared to assess susceptibility to damage. We compared tip widths of balloons of different nominal inflation diameters. We examined stents after side-branch access for distortion. In 42 of 48 (88%) of balloon tips from patients with resistance to or failure to cross through the side of a stent there was tip damage. Even when the balloon crossed without perceptible resistance, tip damage occurred in over half of balloons 18/34 (53%). Some balloon designs were more resistant to damage than others. Tips from balloons of different nominal diameters from the same manufacturer had the same width. Stent distortion caused by damaged balloon tips is improved by kissing balloon post-dilatation. CONCLUSIONS: Balloon tip damage is common with crossing between stent struts. This is one cause of failure of a balloon to access a side-branch and a new balloon should be used. If stent distortion is suspected, it should be corrected with kissing balloon post-dilatation.

Systemic Error in Radiology.

OBJECTIVE: Interpretive errors in diagnostic imaging result in significant patient morbidity and mortality, but the importance of errors and process failures in the imaging cycle other than during image interpretation is underappreciated. In this article, we describe these errors and potential solutions, providing a framework to improve patient safety and understand the changing roles of radiologists beyond image interpretation. CONCLUSION: For comprehensive improvements to health care delivery, other failures in the cycle besides diagnostic interpretive error-such as ordering inappropriate studies, PACS failures, and a lack of accurate clinician contact information (with resultant communication failure)-should be recognized as contributors to patient harm because they lead to wasted resources and delayed care. By taking ownership of the entire imaging cycle, radiologists can increase their net worth to patient care and cement their roles as experts in the effective, evidence-based use of imaging technologies.

Interpretive Error in Radiology.

OBJECTIVE: Although imaging technology has advanced significantly since the work of Garland in 1949, interpretive error rates remain unchanged. In addition to patient harm, interpretive errors are a major cause of litigation and distress to radiologists. In this article, we discuss the mechanics involved in searching an image, categorize omission errors, and discuss factors influencing diagnostic accuracy. Potential individual- and system-based solutions to mitigate or eliminate errors are also discussed. CONCLUSION: Radiologists use visual detection, pattern recognition, memory, and cognitive reasoning to synthesize final interpretations of radiologic studies. This synthesis is performed in an environment in which there are numerous extrinsic distractors, increasing workloads and fatigue. Given the ultimately human task of perception, some degree of error is likely inevitable even with experienced observers. However, an understanding of the causes of interpretive errors can help in the development of tools to mitigate errors and improve patient safety.

Genome wide analysis reveals single nucleotide polymorphisms associated with fatness and putative novel copy number variants in three pig breeds.

BACKGROUND: Obesity, excess fat tissue in the body, can underlie a variety of medical complaints including heart disease, stroke and cancer. The pig is an excellent model organism for the study of various human disorders, including obesity, as well as being the foremost agricultural species. In order to identify genetic variants associated with fatness, we used a selective genomic approach sampling DNA from animals at the extreme ends of the fat and lean spectrum using estimated breeding values derived from a total population size of over 70,000 animals. DNA from 3 breeds (Sire Line Large White, Duroc and a white Pietrain composite line (Titan)) was used to interrogate the Illumina Porcine SNP60 Genotyping Beadchip in order to identify significant associations in terms of single nucleotide polymorphisms (SNPs) and copy number variants (CNVs). RESULTS: By sampling animals at each end of the fat/lean EBV (estimate breeding value) spectrum the whole population could be assessed using less than 300 animals, without losing statistical power. Indeed, several significant SNPs (at the 5% genome wide significance level) were discovered, 4 of these linked to genes with ontologies that had previously been correlated with fatness (NTS, FABP6, SST and NR3C2). Quantitative analysis of the data identified putative CNV regions containing genes whose ontology suggested fatness related functions (MCHR1, PPARα, SLC5A1 and SLC5A4). CONCLUSIONS: Selective genotyping of EBVs at either end of the phenotypic spectrum proved to be a cost effective means of identifying SNPs and CNVs associated with fatness and with estimated major effects in a large population of animals.

Chest computed tomography features predictive of elevated B-type natriuretic peptide independent of renal function: diagnostic implications for evaluation of congestive heart failure.

OBJECTIVE: B-type natriuretic peptide (BNP), commonly evaluated in patients suspected of congestive heart failure, is also elevated in patients with renal insufficiency. The objective of our study was to identify chest computed tomography features that correlate with BNP levels independent of renal function. MATERIALS AND METHODS: A total of 162 (of which 76 had normal BNP and 86 had elevated BNP) patients with chest computed tomography and serum BNP levels measured within 24 hours were evaluated for the presence of ground-glass opacities, interlobular septal thickening, mediastinal lymphadenopathy, mosaic perfusion, peribronchovascular thickening, pericardial effusion, and pleural effusion. Both univariate and multivariate analysis were used to correlate these features with the serum BNP. Multiple logistic regression was used to identify statistically significant correlates of BNP controlling for the glomerular filtration rate. RESULTS: Ground-glass opacity, interlobular septal thickening, pericardial effusion, and left- and right-sided pleural effusion were statistically significant predictors of elevated BNP on separate logistic regression incorporating the glomerular filtration rate. After multiple logistic regression, interlobular septal thickening (odds ratio, 5.69) and pleural effusion (odds ratio, 3.88) remained significant predictors of BNP independent of the glomerular filtration rate. CONCLUSIONS: Interlobular septal thickening and pleural effusion appear to be independent predictors of BNP, and this may be useful in the evaluation of patients for congestive heart failure in the setting of renal insufficiency.

Revised spectral metrics for body surface measurements of gastric electrophysiology.

BACKGROUND: Electrogastrography (EGG) non-invasively evaluates gastric function but has not achieved common clinical adoption due to several technical limitations. Body Surface Gastric Mapping (BSGM) has been introduced to overcome these limitations, but pitfalls in traditional metrics used to analyze spectral data remain unaddressed. This study critically evaluates five traditional EGG metrics and introduces improved BSGM spectral metrics, with validation in a large cohort. METHODS: Pitfalls in five EGG metrics were assessed (dominant frequency, percentage time normogastria, amplitude, power ratio, and instability coefficient), leading to four revised BSGM spectral metrics. Traditional and revised metrics were compared to validate performance using a standardized 100-subject database of BSGM tests (30 min baseline; 4-h postprandial) recorded using Gastric Alimetry® (Alimetry). KEY RESULTS: BMI and amplitude were highly correlated (r = -0.57, p < 0.001). We applied a conservative BMI correction to obtain a BMI-adjusted amplitude metric (r = -0.21, p = 0.037). Instability coefficient was highly correlated with both dominant frequency (r = -0.44, p < 0.001), and percent bradygastria (r = 0.85, p < 0.001), in part due to misclassification of low frequency transients as gastric activity. This was corrected by introducing distinct gastric frequency and stability metrics (Principal Gastric Frequency and Gastric Alimetry Rhythm Index (GA-RI)TM ) that were uncorrelated (r = 0.14, p = 0.314). Only 28% of subjects showed a maximal averaged amplitude within the first postprandial hour. Calculating Fed:Fasted Amplitude Ratio over a 4-h postprandial window yielded a median increase of 0.31 (IQR 0-0.64) above the traditional ratio. CONCLUSIONS & INFERENCES: The revised metrics resolve critical pitfalls impairing the performance of traditional EGG, and should be applied in future BSGM spectral analyses.

A novel scalable electrode array and system for non-invasively assessing gastric function using flexible electronics.

BACKGROUND: Disorders of gastric function are highly prevalent, but diagnosis often remains symptom-based and inconclusive. Body surface gastric mapping is an emerging diagnostic solution, but current approaches lack scalability and are cumbersome and clinically impractical. We present a novel scalable system for non-invasively mapping gastric electrophysiology in high-resolution (HR) at the body surface. METHODS: The system comprises a custom-designed stretchable high-resolution "peel-and-stick" sensor array (8 × 8 pre-gelled Ag/AgCl electrodes at 2 cm spacing; area 225 cm2 ), wearable data logger with custom electronics incorporating bioamplifier chips, accelerometer and Bluetooth synchronized in real-time to an App with cloud connectivity. Automated algorithms filter and extract HR biomarkers including propagation (phase) mapping. The system was tested in a cohort of 24 healthy subjects to define reliability and characterize features of normal gastric activity (30 m fasting, standardized meal, and 4 h postprandial). KEY RESULTS: Gastric mapping was successfully achieved non-invasively in all cases (16 male; 8 female; aged 20-73 years; BMI 24.2 ± 3.5). In all subjects, gastric electrophysiology and meal responses were successfully captured and quantified non-invasively (mean frequency 2.9 ± 0.3 cycles per minute; peak amplitude at mean 60 m postprandially with return to baseline in <4 h). Spatiotemporal mapping showed regular and consistent wave activity of mean direction 182.7° ± 73 (74.7% antegrade, 7.8% retrograde, 17.5% indeterminate). CONCLUSIONS AND INFERENCES: BSGM is a new diagnostic tool for assessing gastric function that is scalable and ready for clinical applications, offering several biomarkers that are improved or new to gastroenterology practice.

Gastric Alimetry ® improves patient phenotyping in gastroduodenal disorders compared to gastric emptying scintigraphy alone.

Objectives: Gastric emptying testing (GET) assesses gastric motility, however is non-specific and insensitive for neuromuscular disorders. Gastric Alimetry® (GA) is a new medical device combining non-invasive gastric electrophysiological mapping and validated symptom profiling. This study assessed patient-specific phenotyping using GA compared to GET. Methods: Patients with chronic gastroduodenal symptoms underwent simultaneous GET and GA, comprising a 30-minute baseline, 99m TC-labelled egg meal, and 4-hour postprandial recording. Results were referenced to normative ranges. Symptoms were profiled in the validated GA App and phenotyped using rule-based criteria based on their relationships to the meal and gastric activity: i) sensorimotor; ii) continuous; and iii) other. Results: 75 patients were assessed; 77% female. Motility abnormality detection rates were: GET 22.7% (14 delayed, 3 rapid); GA spectral analysis 33.3% (14 low rhythm stability / low amplitude; 5 high amplitude; 6 abnormal frequency); combined yield 42.7%. In patients with normal spectral analysis, GA symptom phenotypes included: sensorimotor 17% (where symptoms strongly paired with gastric amplitude; median r=0.61); continuous 30%; other 53%. GA phenotypes showed superior correlations with GCSI, PAGI-SYM, and anxiety scales, whereas Rome IV Criteria did not correlate with psychometric scores (p>0.05). Delayed emptying was not predictive of specific GA phenotypes. Conclusions: GA improves patient phenotyping in chronic gastroduodenal disorders in the presence and absence of motility abnormalities with improved correlation with symptoms and psychometrics compared to gastric emptying status and Rome IV criteria. These findings have implications for the diagnostic profiling and personalized management of gastroduodenal disorders. Study Highlights: 1) WHAT IS KNOWN Chronic gastroduodenal symptoms are common, costly and greatly impact on quality of lifeThere is a poor correlation between gastric emptying testing (GET) and symptomsGastric Alimetry® is a new medical device combining non-invasive gastric electrophysiological mapping and validated symptom profiling 2) WHAT IS NEW HERE Gastric Alimetry generates a 1.5x higher yield for motility abnormalities than GETWith symptom profiling, Gastric Alimetry identified 2.7x more specific patient categories than GETGastric Alimetry improves clinical phenotyping, with improved correlation with symptoms and psychometrics compared to GET.

Testing alternative models and predictive utility of the Death Anxiety Inventory-Revised: A COVID-19 related longitudinal population based study.

The beginning of the COVID-19 pandemic had a profound effect on all aspects of daily life and triggered a swell of anxiety across the world. Some suggest this emotional response to the pandemic can be explained through death anxiety (DA), a transdiagnostic dimension associated with numerous psychological disorders. However, it remains unclear as to whether DA is a unidimensional or multidimensional construct. The primary aim of this study was to examine the underlying structure of the Death Anxiety Inventory-Revised (DAI-R; Tomás-Sábado et al., 2005) and assess its associations with mental health and demographic variables during the COVID-19 pandemic. To achieve these aims, we utilized data from Waves 1 (N = 2205: collected between March 23 and March 28, 2020) and 2 (N = 1406: collected between April 22 and May 1, 2020) of the COVID-19 Psychological Research Consortium (C19PRC), a multi-wave nationally representative study. Results showed that a 4-factor model provided the best fit to the data compared to a unidimensional and 4-factor second-order model. Further analyses showed that DA at Wave 1 was positively associated with somatic symptoms, paranoia, depression, anxiety, and traumatic stress symptoms at Wave 2, supporting previous research that suggests that the fear of death is predictive of psychopathology. Significantly, the factor labelled 'Thoughts about Death' at Wave 1 was the strongest predictor of the five main psychological variables at Wave 2, after statistically controlling for the other latent variables. These findings highlight the transdiagnostic nature of DA and support this important diagnostic construct becoming a measure of mental health more generally within the population. It is hoped that this research will shine a light on those suffering from DA and become a catalyst for increased therapeutic intervention, funding, and research in this area.

An automated artifact detection and rejection system for body surface gastric mapping.

BACKGROUND: Body surface gastric mapping (BSGM) is a new clinical tool for gastric motility diagnostics, providing high-resolution data on gastric myoelectrical activity. Artifact contamination was a key challenge to reliable test interpretation in traditional electrogastrography. This study aimed to introduce and validate an automated artifact detection and rejection system for clinical BSGM applications. METHODS: Ten patients with chronic gastric symptoms generated a variety of artifacts according to a standardized protocol (176 recordings) using a commercial BSGM system (Alimetry, New Zealand). An automated artifact detection and rejection algorithm was developed, and its performance was compared with a reference standard comprising consensus labeling by 3 analysis experts, followed by comparison with 6 clinicians (3 untrained and 3 trained in artifact detection). Inter-rater reliability was calculated using Fleiss' kappa. KEY RESULTS: Inter-rater reliability was 0.84 (95% CI:0.77-0.90) among experts, 0.76 (95% CI:0.68-0.83) among untrained clinicians, and 0.71 (95% CI:0.62-0.79) among trained clinicians. The sensitivity and specificity of the algorithm against experts was 96% (95% CI:91%-100%) and 95% (95% CI:90%-99%), respectively, vs 77% (95% CI:68%-85%) and 99% (95% CI:96%-100%) against untrained clinicians, and 97% (95% CI:92%-100%) and 88% (95% CI:82%-94%) against trained clinicians. CONCLUSIONS & INFERENCES: An automated artifact detection and rejection algorithm was developed showing >95% sensitivity and specificity vs expert markers. This algorithm overcomes an important challenge in the clinical translation of BSGM and is now being routinely implemented in patient test interpretations.

Standardized system and App for continuous patient symptom logging in gastroduodenal disorders: Design, implementation, and validation.

BACKGROUND: Functional gastroduodenal disorders include functional dyspepsia, chronic nausea and vomiting syndromes, and gastroparesis. These disorders are common, but their overlapping symptomatology poses challenges to diagnosis, research, and therapy. This study aimed to introduce and validate a standardized patient symptom-logging system and App to aid in the accurate reporting of gastroduodenal symptoms for clinical and research applications. METHODS: The system was implemented in an iOS App including pictographic symptom illustrations, and two validation studies were conducted. To assess convergent and concurrent validity, a diverse cohort with chronic gastroduodenal symptoms undertook App-based symptom logging for 4 h after a test meal. Individual and total post-prandial symptom scores were averaged and correlated against two previously validated instruments: PAGI-SYM (for convergent validity) and PAGI-QOL (for concurrent validity). To assess face and content validity, semi-structured qualitative interviews were conducted with patients. KEY RESULTS: App-based symptom reporting demonstrated robust convergent validity with PAGI-SYM measures of nausea (rS  =0.68), early satiation (rS  =0.55), bloating (rS  =0.48), heartburn (rS  =0.47), upper gut pain (rS  =0.40), and excessive fullness (rS  =0.40); all p < 0.001 (n = 79). The total App-reported Gastric Symptom Burden Score correlated positively with PAGI-SYM (rS  =0.56; convergent validity; p < 0.001), and negatively with PAGI-QOL (rS  = -0.34; concurrent validity; p = 0.002). Interviews demonstrated that the pictograms had adequate face and content validity. CONCLUSIONS AND INFERENCES: The continuous patient symptom-logging App demonstrated robust convergent, concurrent, face, and content validity when used within a 4-h post-prandial test protocol. The App will enable standardized symptom reporting and is anticipated to provide utility in both research and clinical practice.

Gastric dysfunction in patients with chronic nausea and vomiting syndromes defined by a noninvasive gastric mapping device.

Chronic nausea and vomiting syndromes (NVSs) are prevalent and debilitating disorders. Putative mechanisms include gastric neuromuscular disease and dysregulation of brain-gut interaction, but clinical tests for objectively defining gastric motor function are lacking. A medical device enabling noninvasive body surface gastric mapping (BSGM) was developed and applied to evaluate NVS pathophysiology. BSGM was performed in 43 patients with NVS and 43 matched controls using Gastric Alimetry (Alimetry), a conformable high-resolution array (8 × 8 electrodes; 20-mm interelectrode spacing), wearable reader, and validated symptom-logging app. Continuous measurement encompassed a fasting baseline (30 minutes), 482-kilocalorie meal, and 4-hour postprandial recording, followed by spectral and spatial biomarker analyses. Meal responses were impaired in NVS, with reduced amplitudes compared to controls (median, 23.3 microvolts versus 38.0 microvolts, P < 0.001), impaired fed-fasting power ratios (1.1 versus 1.6, P = 0.02), and disorganized slow waves (spatial frequency stability, 13.6 versus 49.5; P < 0.001). Two distinct NVS subgroups were evident with indistinguishable symptoms (all P > 0.05). Most patients (62%) had normal BSGM studies with increased psychological comorbidities (43.5% versus 7.7%; P = 0.03) and anxiety scores (median, 16.5 versus 13.0; P = 0.035). A smaller subgroup (31%) had markedly abnormal BSGM, with biomarkers correlating with symptoms (nausea, pain, excessive fullness, early satiety, and bloating; all r > 0.35, P < 0.05). Patients with NVS share overlapping symptoms but comprise distinct underlying phenotypes as revealed by a BSGM device. These phenotypes correlate with symptoms, which should inform clinical management and therapeutic trial design.

Restricting Daily Chest Radiography in the Intensive Care Unit: Implementing Evidence-Based Medicine to Decrease Utilizationt.

PURPOSE: In this study, the authors applied evidence-based medicine to decrease the utilization of routine chest radiography in adult intensive care units and used time-driven activity-based costing to demonstrate cost savings. METHODS: A multidisciplinary team was formed with representatives from radiology, surgery, internal medicine, and nursing. The process of performing a portable chest radiographic examination was mapped, and time trials were performed by the radiology technologists and radiology resident. This information was used to determine the cost of performing portable intensive care unit (ICU) chest radiographic studies. The clinical team changed resident education, ordering protocols, and workflows to discontinue the use of routine daily chest radiography, emphasizing that it should be ordered only in specific situations, such as on admission or after central line placement. In addition, as a balancing measure, the team tracked complications such as unplanned extubations and ventilator days. RESULTS: Changing ordering practices in the adult ICUs to align with established evidence-based guidelines resulted in a 37% decrease in the utilization of portable chest radiography between June and December, without a concomitant increase in unplanned extubations or ventilator days. In addition, a proportionate cost savings was realized, as demonstrated by the application of time-driven activity-based costing. CONCLUSIONS: This performance improvement initiative successfully increased the value of care delivered to ICU patients by aligning institutional clinical practice with evidence-based medicine. This resulted in decreased utilization and the cost associated with delivering care without a concomitant increase in complications.