Eosinophilic esophagitis: Does age matter?

OBJECTIVES: Eosinophilic esophagitis (EoE) is often diagnosed in school-age children between 6- and 9-year-old. There is less known about those who are diagnosed with EoE that are younger than 6 years old. The objective of this study is to compare clinical presentation, comorbidities, and outcomes based on age at diagnosis of EoE. METHODS: Single-center retrospective chart review of children (<18 years) diagnosed with EoE between 2005 and 2020. We recorded demographics, clinical presentation, family history, past medical history, treatment, and endoscopic findings. Children in this cohort were classified based on age into three age groups: <2 years, 2-<6 years, and 6-<18 years. RESULTS: We identified 256 children with EoE, the mean age (SD) at the time of diagnosis was 9 (5.2) years and 184 (72%) were male. We had 164 (64%) patients with available follow-up esophagogastroduodenoscopies (EGDs) data (495 EGDs in total) of those 99/164 (60%) reached mucosal remission. In the very young children (<2 years) vomiting was the most common presentation, while poor weight gain was seen more in the 2-<6-year group in comparison to the >6-years. Food impaction and abdominal pain were most likely to present in older children 6-18 years. Combination therapy, as opposed to a single therapy, induced remission at a higher frequency in the <6-year group in comparison to the 6-<18-year group (85% vs. 66%). CONCLUSION: EoE should be considered in younger children presenting with feeding difficulty and poor weight gain. Combination therapy seems to be more effective in younger children with EoE, but further studies with bigger sample size are needed to study the efficacy of the different combination therapies.

Performance of an Artificial Intelligence Model for Recognition and Quantitation of Histologic Features of Eosinophilic Esophagitis on Biopsy Samples.

We have developed an artificial intelligence (AI)-based digital pathology model for the evaluation of histologic features related to eosinophilic esophagitis (EoE). In this study, we evaluated the performance of our AI model in a cohort of pediatric and adult patients for histologic features included in the Eosinophilic Esophagitis Histologic Scoring System (EoEHSS). We collected a total of 203 esophageal biopsy samples from patients with mucosal eosinophilia of any degree (91 adult and 112 pediatric patients) and 10 normal controls from a prospectively maintained database. All cases were assessed by a specialized gastrointestinal (GI) pathologist for features in the EoEHSS at the time of original diagnosis and rescored by a central GI pathologist (R.K.M.). We subsequently analyzed whole-slide image digital slides using a supervised AI model operating in a cloud-based, deep learning AI platform (Aiforia Technologies) for peak eosinophil count (PEC) and several histopathologic features in the EoEHSS. The correlation and interobserver agreement between the AI model and pathologists (Pearson correlation coefficient [rs] = 0.89 and intraclass correlation coefficient [ICC] = 0.87 vs original pathologist; rs = 0.91 and ICC = 0.83 vs central pathologist) were similar to the correlation and interobserver agreement between pathologists for PEC (rs = 0.88 and ICC = 0.91) and broadly similar to those for most other histologic features in the EoEHSS. The AI model also accurately identified PEC of >15 eosinophils/high-power field by the original pathologist (area under the curve [AUC] = 0.98) and central pathologist (AUC = 0.98) and had similar AUCs for the presence of EoE-related endoscopic features to pathologists' assessment. Average eosinophils per epithelial unit area had similar performance compared to AI high-power field-based analysis. Our newly developed AI model can accurately identify, quantify, and score several of the main histopathologic features in the EoE spectrum, with agreement regarding EoEHSS scoring which was similar to that seen among GI pathologists.

Clinical Implications for Children Developing Direct Hyperbilirubinemia on Extracorporeal Membrane Oxygenation.

OBJECTIVE: Extracorporeal membrane oxygenation (ECMO)-associated direct hyperbilirubinemia (DHB) is likely multifactorial. The objective of this study is to assess the frequency and risk factors for developing direct hyperbilirubinemia while on ECMO, and its implication on the mortality of children. METHODS: We performed a retrospective study between January 2010 and January 2020. Using Mayo Clinic electronic health record, we identified children (<18 years) who required veno-arterial (VA) ECMO support. Demographics, ECMO indication, laboratory findings, and outcomes were abstracted. Illness acuity scores, including vasoactive-ionotropic score (VIS), were used to assess disease severity at time of admission. Study cohort was divided into two groups: children who developed direct hyperbilirubinemia (DHB) on ECMO and children who did not (control). DHB was defined as direct bilirubin (DB) of >1.0 mg/dL. Disease acuity and mortality rates were compared between the two groups. Logistic regression was used to analyze the risk of mortality independent of potential confounding variables. RESULTS: We identified 106 children who required ECMO support during the study period. Of those, 36 (34%) children developed DHB on ECMO. Illness acuity scores were significantly higher in the DHB group on ECMO day 2 (P = 0.046) and day 7 (P = 0.01). Mortality rate was higher in the DHB group 72%, versus 29% in the control group (P < 0.001). CONCLUSION: DHB was associated with a higher mortality rate than the control group.

The Use of Virtual Reality Echocardiography in Medical Education.

Virtual reality (VR) is a relatively new technology that allows an individual to experience a virtual world. This new immersive video type may be of particular usefulness in procedure-based healthcare settings. We hypothesized that VR echocardiography was non-inferior to live demonstration. Our aim was to assess the usefulness of a VR echocardiographic approach in teaching echocardiography to pediatric trainees compared to live demonstration. This was a single center, cross-sectional observational design. We used a Garmin VIRB® 360 and a head-mount display to record live echocardiography exams in a pediatric population. An Oculus Go™ was used to view the 360° immersive/VR videos. Trainees responded to a written questionnaire afterwards. Fifteen trainees participated in the study, each of whom had previously seen echocardiography through live demonstration teaching. Eleven respondents had previous hands-on echocardiography experience. All 15 participants confirmed that VR echocardiography is a useful teaching tool with 87% (n = 13) rating it as good or very good on a 5-point Likert scale. When asked to compare VR to live demonstration, 67% (n = 10) rated VR echocardiography as the same or better than live demonstration. One of the participants reported a side effect, namely mild and self-resolving dizziness. VR echocardiography is a safe, inexpensive and practical way for trainees to learn echocardiography. The addition of VR echocardiography to the arsenal of teaching tools may enrich the learning experience for trainees.

Detection of Neisseria meningitidis in a paediatric patient with septic arthritis using multiplexed diagnostic PCR targeting meningitis/encephalitis (ME).

BACKGROUND: Neisseria meningitidis is associated with meningitis and septicemia. Septic meningococcal arthritis is relatively uncommon and its diagnosis associated with clinical and microbiological challenges. Early recognition and treatment is required to prevent joint destruction. PURPOSE: We describe a case of an eleven-year-old boy with septic arthritis and the first reported use of a multiplexed diagnostic PCR test, capable of simultaneous rapid detection of 14 pathogens directly from CSF samples, to determine presence of N. meningitides in a synovial fluid sample. RESULTS: In this case, blood cultures and an aspiration of the joint fluid were negative for microbial growth, but leucocytes were present. Analysis of samples using the multiplexed FilmArray® meningitis/encephalitis panel (MEP) proved positive for N. meningitidis. In parallel, samples forwarded to an accredited reference laboratory confirmed the findings by bacterial 16S rRNA gene amplification and sequencing. Subsequent to these results, empiric treatment with intravenous flucloxacillin was discontinued and oral amoxicillin administered for 1 month. The status of the patient improved with etiology-based antimicrobial therapy. CONCLUSIONS: This case demonstrates difficulties associated with clinical and microbiological diagnosis of primary septic meningococcal arthritis. We describe the first successful use of the FilmArray® MEP assay in detection of N. meningitidis in that context.

A Novel Selectable Islet 1 Positive Progenitor Cell Reprogrammed to Expandable and Functional Smooth Muscle Cells.

Disorders affecting smooth muscle structure/function may require technologies that can generate large scale, differentiated and contractile smooth muscle cells (SMC) suitable for cell therapy. To date no clonal precursor population that provides large numbers of differentiated SMC in culture has been identified in a rodent. Identification of such cells may also enhance insight into progenitor cell fate decisions and the relationship between smooth muscle precursors and disease states that implicate differentiated SMC. In this study, we used classic clonal expansion techniques to identify novel self-renewing Islet 1 (Isl-1) positive primitive progenitor cells (PPC) within rat bone marrow that exhibited canonical stem cell markers and preferential differentiation towards a smooth muscle-like fate. We subsequently used molecular tagging to select Isl-1 positive clonal populations from expanded and de novo marrow cell populations. We refer to these previously undescribed cells as the PPC given its stem cell marker profile, and robust self-renewal capacity. PPC could be directly converted into induced smooth muscle cells (iSMC) using single transcription factor (Kruppel-like factor 4) knockdown or transactivator (myocardin) overexpression in contrast to three control cells (HEK 293, endothelial cells and mesenchymal stem cells) where such induction was not possible. iSMC exhibited immuno- and cytoskeletal-phenotype, calcium signaling profile and contractile responses similar to bona fide SMC. Passaged iSMC could be expanded to a scale sufficient for large scale tissue replacement. PPC and reprogramed iSMC so derived may offer future opportunities to investigate molecular, structure/function and cell-based replacement therapy approaches to diverse cardiovascular, respiratory, gastrointestinal, and genitourinary diseases that have as their basis smooth muscle cell functional aberrancy or numerical loss. Stem Cells 2016;34:1354-1368.

Synthetic chemically modified mrna-based delivery of cytoprotective factor promotes early cardiomyocyte survival post-acute myocardial infarction.

To extend the temporal window for cytoprotection in cardiomyocytes undergoing apoptosis after hypoxia and myocardial infarction (MI), a synthetic chemically modified mRNA (modRNA) was used to drive delivery of insulin-like growth factor-1 (IGF1) within the area at risk in an in vivo murine model of MI. Delivery of IGF1 modRNA, with a polyethylenimine-based nanoparticle, augmented secreted and cell-associated IGF1, promoting cardiomyocyte survival and abrogating cell apoptosis under hypoxia-induced apoptosis conditions. Translation of modRNA-IGF1 was sufficient to induce downstream increases in the levels of Akt and Erk phosphorylation. Downregulation of IGF1 specific miRNA-1 and -133 but not miR-145 expression was also confirmed. As a proof of concept, intramyocardial delivery of modRNA-IGF1 but not control modRNA-GFP significantly decreased the level of TUNEL positive cells, augmented Akt phosphorylation, and decreased caspase-9 activity within the infarct border zone 24 h post-MI. These findings demonstrate the potential for an extended cytoprotective effect of transient IGF1 driven by synthetic modRNA delivery.

Pediatric sex estimation using AI-enabled ECG analysis: influence of pubertal development.

AI-enabled ECGs have previously been shown to accurately predict patient sex in adults and correlate with sex hormone levels. We aimed to test the ability of AI-enabled ECGs to predict sex in the pediatric population and study the influence of pubertal development. AI-enabled ECG models were created using a convolutional neural network trained on pediatric 10-second, 12-lead ECGs. The first model was trained de novo using pediatric data. The second model used transfer learning from a previously validated adult data-derived algorithm. We analyzed the first ECG from 90,133 unique pediatric patients (aged ≤18 years) recorded between 1987-2022, and divided the cohort into training, validation, and testing datasets. Subgroup analysis was performed on prepubertal (0-7 years), peripubertal (8-14 years), and postpubertal (15-18 years) patients. The cohort was 46.7% male, with 21,678 prepubertal, 26,740 peripubertal, and 41,715 postpubertal children. The de novo pediatric model demonstrated 81% accuracy and an area under the curve (AUC) of 0.91. Model sensitivity was 0.79, specificity was 0.83, positive predicted value was 0.84, and the negative predicted value was 0.78, for the entire test cohort. The model's discriminatory ability was highest in postpubertal (AUC = 0.98), lower in the peripubertal age group (AUC = 0.91), and poor in the prepubertal age group (AUC = 0.67). There was no significant performance difference observed between the transfer learning and de novo models. AI-enabled interpretation of ECG can estimate sex in peripubertal and postpubertal children with high accuracy.

Impact of heart failure on reoperation in adult congenital heart disease: An innovative machine learning model.

OBJECTIVES: The study objectives were to evaluate the association between preoperative heart failure and reoperative cardiac surgical outcomes in adult congenital heart disease and to develop a risk model for postoperative morbidity/mortality. METHODS: Single-institution retrospective cohort study of adult patients with congenital heart disease undergoing reoperative cardiac surgery between January 1, 2010, and March 30, 2022. Heart failure defined clinically as preoperative diuretic use and either New York Heart Association Class II to IV or systemic ventricular ejection fraction less than 40%. Composite outcome included operative mortality, mechanical circulatory support, dialysis, unplanned noncardiac reoperation, persistent neurologic deficit, and cardiac arrest. Multivariable logistic regression and machine learning analysis using gradient boosting technology were performed. Shapley statistics determined feature influence, or impact, on model output. RESULTS: Preoperative heart failure was present in 376 of 1011 patients (37%); those patients had longer postoperative length of stay (6 [5-8] vs 5 [4-7] days, P < .001), increased postoperative mechanical circulatory support (21/376 [6%] vs 16/635 [3%], P = .015), and decreased long-term survival (84% [80%-89%] vs 90% [86%-93%]) at 10 years (P = .002). A 7-feature machine learning risk model for the composite outcome achieved higher area under the curve (0.76) than logistic regression, and ejection fraction was most influential (highest mean |Shapley value|). Additional risk factors for the composite outcome included age, number of prior cardiopulmonary bypass operations, urgent/emergency procedure, and functionally univentricular physiology. CONCLUSIONS: Heart failure is common among adult patients with congenital heart disease undergoing cardiac reoperation and associated with longer length of stay, increased postoperative mechanical circulatory support, and decreased long-term survival. Machine learning yields a novel 7-feature risk model for postoperative morbidity/mortality, in which ejection fraction was the most influential.

Development and technical validation of an artificial intelligence model for quantitative analysis of histopathologic features of eosinophilic esophagitis.

Background: In an attempt to provide quantitative, reproducible, and standardized analyses in cases of eosinophilic esophagitis (EoE), we have developed an artificial intelligence (AI) digital pathology model for the evaluation of histologic features in the EoE/esophageal eosinophilia spectrum. Here, we describe the development and technical validation of this novel AI tool. Methods: A total of 10 726 objects and 56.2 mm2 of semantic segmentation areas were annotated on whole-slide images, utilizing a cloud-based, deep learning artificial intelligence platform (Aiforia Technologies, Helsinki, Finland). Our training set consisted of 40 carefully selected digitized esophageal biopsy slides which contained the full spectrum of changes typically seen in the setting of esophageal eosinophilia, ranging from normal mucosa to severe abnormalities with regard to each specific features included in our model. A subset of cases was reserved as independent "test sets" in order to assess the validity of the AI model outside the training set. Five specialized experienced gastrointestinal pathologists scored each feature blindly and independently of each other and of AI model results. Results: The performance of the AI model for all cell type features was similar/non-inferior to that of our group of GI pathologists (F1-scores: 94.5-94.8 for AI vs human and 92.6-96.0 for human vs human). Segmentation area features were rated for accuracy using the following scale: 1. "perfect or nearly perfect" (95%-100%, no significant errors), 2. "very good" (80%-95%, only minor errors), 3. "good" (70%-80%, significant errors but still captures the feature well), 4. "insufficient" (less than 70%, significant errors compromising feature recognition). Rating scores for tissue (1.01), spongiosis (1.15), basal layer (1.05), surface layer (1.04), lamina propria (1.15), and collagen (1.11) were in the "very good" to "perfect or nearly perfect" range, while degranulation (2.23) was rated between "good" and "very good". Conclusion: Our newly developed AI-based tool showed an excellent performance (non-inferior to a group of experienced GI pathologists) for the recognition of various histologic features in the EoE/esophageal mucosal eosinophilia spectrum. This tool represents an important step in creating an accurate and reproducible method for semi-automated quantitative analysis to be used in the evaluation of esophageal biopsies in this clinical context.

Assessment of the FilmArray® multiplex PCR system and associated meningitis/encephalitis panel in the diagnostic service of a tertiary hospital.

Rapid and accurate diagnosis of meningitis/encephalitis (M/E) is essential for successful patient outcomes. The FilmArray® meningitis/encephalitis Panel (MEP) is a multiplexed PCR test for simultaneous, rapid detection of pathogens directly from cerebrospinal fluid (CSF) samples. 94 prospectively collected CSF specimens from patients with clinical suspicion of infective M/E underwent testing for 14 pathogens simultaneously, including Escherichia coli, Haemophilus influenzae, Neisseria meningitidis, and Varicella zoster. MEP demonstrated 95% agreement with current PCR methods, resulting in 16 diagnosed cases of M/E. Typically, the FilmArray® MEP results were delivered within approximately one hour, contrasting with current practices taking up to 5.6 days. Given the significant morbidity and mortality associated with delayed diagnosis of central nervous system infections, the FilmArray® MEP is a useful addition to the diagnostic capabilities of a clinical microbiology department.

Effects of Introducing a Secure Web-based Messenger Application for Communication Among Non-consultant Hospital Doctors (NCHDs).

INTRODUCTION:  Use of web-based messaging applications to communicate clinical information is common between non-consultant hospital doctors (NCHDs). This study sought to assess web-based messenger use in NCHDs following the introduction of a more secure alternative to WhatsApp (WhatsApp, Inc., Menlo Park, CA, USA). METHODS:  A 10-item survey was undertaken on two NCHD cohorts. The second cohort received training on data protection and an alternative application to WhatsApp. Quantitative data analysis was conducted using the IBM Statistical Package for Social Sciences (SPSS) (IBM SPSS Statistics, Armonk, NY). RESULTS:  The total response rate across both groups was 63% (N = 68). The majority of respondents used WhatsApp to communicate clinical information. In the second cohort, fewer NCHDs shared identifiable sensitive patient information 97% (n = 29/30) vs 81% (n = 25/31) and fewer NCHDs shared/stored clinical images. DISCUSSION:  WhatsApp use is common among NCHDs. An alternative means of communication can improve the safety of patient data. NCHDs require more training on data protection laws and their own responsibilities.

Medical school selection criteria as predictors of medical student empathy: a cross-sectional study of medical students, Ireland.

OBJECTIVES: To determine whether performance in any of the Health Professions Admissions Test (HPAT) sections, most specifically the interpersonal understanding section, correlates with self-reported empathy levels in medical students. SETTING: The study was conducted in University College Cork, Ireland. PARTICIPANTS: 290 students participated in the study. Matching HPAT scores were available for 263 students. All male and female undergraduate students were invited to participate. Postgraduate and international students were excluded. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary measures: HPAT-Ireland and Jefferson Scale of Physician Empathy (JSE) scores were compared including subsection analysis. Secondary measures: comparisons were made between groups such as gender and year of programme. RESULTS: A total of 290 students participated. Males scored significantly higher than females for total HPAT-Ireland (U=7329, z=-2.04, p<0.05), HPAT-Ireland section 1 (U=5382, z=-5.21, p<0.001) and section 3 scores (U=6833, z=-2.85, p<0.01). In contrast, females scored significantly higher than males on HPAT-Ireland section 2 (U=5844, z=-4.46, p<0.001). Females demonstrated significantly higher total JSE scores relative to males (mean score ± SEM: 113.33±1.05vs 109.21±0.95; U=8450, z=-2.83, p<0.01). No significant association was observed between JSE scores and any of the HPAT-Ireland measures (all p>0.05). There was no effect of programme year on JSE scores (all p>0.05). CONCLUSION: The introduction of the HPAT-Ireland test was partly designed to identify students with strong interpersonal skills. A significant finding of this study is that JSE values did not correlate with HPAT-Ireland scores. This study suggests no clear link between scores on a selection test, the HPAT-Ireland, which is designed to assess several skill domains including interpersonal skills, and scores on a psychometric measure of empathy, at any point during medical education.