Genetic predictors of inflammation in the risk of occupational asthma in young apprentices

BackgroundThe influence of genetic predictors of inflammation and atopy on occupational asthma in apprentices is not known.ObjectivesTo assess the influence of genetic polymorphisms of IL4RA, IL13, TNFA, IL1A, and IL5 on the decline of lung function and bronchial hyperresponsiveness in a prospective follow-up study of baker/pastry maker and hairdresser apprentices.MethodsA total of 351 apprentices were included in the study. We performed skin testing, spirometry, fractional exhaled nitric oxide measurement, and methacholine hyperreactivity testing at the initial visit and during and at the end of the 18-month training period. Gene variants of IL4RA, IL13, TNFA, IL1A, and IL5 were determined in DNA from nasal lavage.ResultsIL13 R130Q/IL4RA S478P or IL13 R130Q//IL4RA Q551R were significant predictors of the decrease of forced expiratory volume and forced vital capacity (P ≤ .006). Genotype GG of TNFAG308A was associated with bronchial hyperresponsiveness in the whole population and in nonatopic individuals (90.63% vs 9.38%; odds ratio, 3.78; 95% confidence interval, 1.10-12.83). TNFA GA and IL5 CC and TNFA GA and IL1A CC were 2 epistatic predictors of exhaled nitrogen monoxide decrease during follow-up (P = .02 and P = .004, respectively). The association with TNFA GA and IL1A CC was the most significant in nonatopic bakers (P < .001).ConclusionWe evidenced a predicting influence of IL13/IL4RA and TNFA in the early exposure to allergens and irritants that precedes occupational asthma. The significance of the associations in the absence of atopy suggests an influence of the genetics predictors related to inflammatory pathways.     

Echocardiography and Cardiac Magnetic Resonance‐Based Feature Tracking in the Assessment of Myocardial Mechanics in Tetralogy of Fallot: An Intermodality Comparison

We investigated intermodality agreements of strains from two‐dimensional echocardiography (2DE) and cardiac magnetic resonance (CMR) feature tracking (FT) in the assessment of right (RV) and left ventricular (LV) mechanics in tetralogy of Fallot (TOF). Patients were prospectively studied with 2DE and CMR performed contiguously. LV and RV strains were computed separately using 2DE and CMR‐FT. Segmental and global longitudinal strains (GLS) for the LV and RV were measured from four‐chamber views; LV radial (global radial strain [GRS]) and circumferential strains (GCS) measured from short‐axis views. Intermodality and interobserver agreements were examined. In 40 patients (20 TOF, mean age 23 years and 20 adult controls), LV, GCS showed narrowest intermodality limits of agreement (mean percentage error 9.5%), followed by GLS (16.4%). RV GLS had mean intermodality difference of 25.7%. GLS and GCS had acceptable interobserver agreement for the LV and RV with both 2DE and CMR‐FT, whereas GRS had high interobserver and intermodality variability. In conclusion, myocardial strains for the RV and LV derived using currently available 2DE and CMR‐FT software are subject to considerable intermodality variability. For both modalities, LV GCS, LV GLS, and RV GLS are reproducible enough to warrant further investigation of incremental clinical merit.     

Ascertaining Design Requirements for Postoperative Care Transition Interventions

Background  Handoffs or care transitions from the operating room (OR) to intensive care unit (ICU) are fragmented and vulnerable to communication errors. Although protocols and checklists for standardization help reduce errors, such interventions suffer from limited sustainability. An unexplored aspect is the potential role of developing personalized postoperative transition interventions using artificial intelligence (AI)-generated risks. Objectives  This study was aimed to (1) identify factors affecting sustainability of handoff standardization, (2) utilize a human-centered approach to develop design ideas and prototyping requirements for a sustainable handoff intervention, and (3) explore the potential role for AI risk assessment during handoffs. Methods  We conducted four design workshops with 24 participants representing OR and ICU teams at a large medical academic center. Data collection phases were (1) open-ended questions, (2) closed card sorting of handoff information elements, and (3) scenario-based design ideation and prototyping for a handoff intervention. Data were analyzed using thematic analysis. Card sorts were further tallied to characterize handoff information elements as core, flexible, or unnecessary. Results  Limited protocol awareness among clinicians and lack of an interdisciplinary electronic health record (EHR)-integrated handoff intervention prevented long-term sustainability of handoff standardization. Clinicians argued for a handoff intervention comprised of core elements (included for all patients) and flexible elements (tailored by patient condition and risks). They also identified unnecessary elements that could be omitted during handoffs. Similarities and differences in handoff intervention requirements among physicians and nurses were noted; in particular, clinicians expressed divergent views on the role of AI-generated postoperative risks. Conclusion  Current postoperative handoff interventions focus largely on standardization of information transfer and handoff processes. Our design approach allowed us to visualize accurate models of user expectations for effective interdisciplinary communication. Insights from this study point toward EHR-integrated, “flexibly standardized” care transition interventions that can automatically generate a patient-centered summary and risk-based report. Keyword: continuity of care, care transition, requirements analysis and design, handoffs, surgery, anesthesia, intensive and critical care, machine learning     

Myocarditis in Adult-Onset Still’s Disease: Case-Based Review

Clinical Rheumatology - Cardiac involvement in adult-onset Still’s disease (AOSD) usually manifests as a pericardial disease. Myocarditis is uncommon (prevalence of 7%). However, the...