Comparison of Patterns and Demographics of Isolated Traumatic Mandibular Fracture Between Incarcerated and General Populations.

Introduction The management of maxillofacial trauma can be challenging in different unique clinical presentations. While maxillofacial fractures vary in location based on the mechanism of injury, the mandibular fracture is noted to be one of the most common facial fractures. The objective of this study was to explore the differences in injury patterns, outcomes, and demographics of isolated traumatic mandibular fractures between incarcerated and general populations. Methods This retrospective study analyzed consecutive patients presenting for trauma care from January 1, 2010, to December 31, 2020, at the Arrowhead Regional Medical Center (ARMC). Patients 18 years and older were included in this study. Patients diagnosed with mandibular fracture as the primary diagnosis at admission and discharge were identified using the International Classification of Disease, Ninth and Tenth Revision (ICD-9, ICD-10) Code. Patient demographics were extracted from their electronic medical records and included race, marital status, and insurance status. Results A total of 1080 patients with confirmed mandibular fractures were included in the final analysis. Among these patients, 87.5% (n=945) were males, 40% (n=432) of the patients were Hispanic, and the average age was 31.55 years old. The most common mechanism of injury was blunt trauma secondary to assault. Compared to the general population with mandibular fracture, the incarcerated patients with mandibular fracture were more likely to be males (96.1% vs 86.1% for incarcerated population vs. general population respectively, p=0.0005). No other variables were statistically different between these two groups. Conclusion The evidence from this study suggests that the patterns, outcomes, and demographics of mandibular fracture in both incarcerated and general populations are similar.

Co-sensitization between legumes is frequently seen, but variable and not always clinically relevant.

Background: Food allergy to peanut and soybean, both legumes, is highly prevalent. The consumption of other legumes and legume protein isolates, some of which may be considered novel foods, is increasing. This may lead to an increase in sensitization and allergy and may pose a risk for legume-allergic (e.g. peanut and soybean) patients due to cross-reactivity. Objective: This study investigated the frequency of co-sensitization and co-allergy between legumes and the role of different protein families. Methods: Six legume-allergic patient groups were included: peanut (n = 30), soybean (n = 30), lupine (n = 30), green pea (n = 30), lentil (n = 17), bean (n = 9). IgE binding to total extracts, protein fractions (7S/11S globulin, 2S albumin, albumin), and 16 individual proteins from 10 legumes (black lentil, blue lupine, chickpea, faba bean, green lentil, pea, peanut, soybean, white bean, and white lupine) was measured by line blot. Results: Co-sensitization varied from 36.7% to 100%. Mono-sensitization was only found in soybean (16.7%), peanut (10%), and green pea-allergic (3.3%) patients. A high frequency of co-sensitization between the 7S/11S globulin fractions of all 10 legumes and individual 7S and 11S globulins was observed. In peanut and soybean-allergic patients, co-allergies for other legumes were uncommon (≤16,7%), while in green pea, lupine, lentil, and bean-allergic patients co-allergy for peanut (64.7%-77.8%) or soybean (50%-64.7%) was frequently seen. Conclusion: Co-sensitization between legumes was high, but generally not clinically relevant. Co-allergy to other legumes was not often seen in peanut- and soybean allergic patients. The 7S and 11S globulins were likely responsible for the observed co-sensitization.

Accidental allergic reactions to food in adolescents and adults: An overview of the factors involved and implications for prevention.

Accidental allergic reactions to food are one of the major problems in adult patients diagnosed with food allergy. Such reactions occur frequently, are often severe and are associated with higher medical and non-medical costs. The aim of this Perspective is to provide insight into the different factors involved in the occurrence of accidental allergic reactions and to present an overview of practical implications for effective preventive measures. Several factors affect the occurrence of accidental reactions. These factors are related to the patient, health care, or food. The most important patient-related factors are age, social barriers to disclosing their allergy and non-adherence to the elimination diet. With regards to healthcare, the degree to which clinical practice is tailored to the individual patient is an important factor. The major food-related factor is the absence of adequate precautionary allergen labeling (PAL) guidelines. Since many factors are involved in accidental allergic reactions, different preventive strategies are needed. It is highly recommended that health care be tailored to the individual patient, with regard to education about the elimination diet, support on behavioral and psychosocial aspects, usage of shared decision-making and taking into account health literacy. In addition, it is crucial that steps are taken to improve policies and guidelines for PAL.

Low dietary adherence after a positive food challenge in food allergic adults.

BACKGROUND: After a positive food challenge (FC), patients receive dietary advice regarding avoidance of the culprit food. We examined the frequency and variables associated with dietary adherence after a positive FC in adults. METHODS: In this prospective daily practice study, adults with a positive FC were included. After every FC, dietary advice was given consisting of three options: (1) strict avoidance, (2) avoidance but products with precautionary allergen labelling (PAL) allowed and (3) (small) amounts allowed. Questionnaires about dietary adherence and associated variables were completed prior to and 6 months after the FC(s). RESULTS: 41 patients (with 58 positive FCs) were included. Overall, patients adhered to the advised diet after 31% of the FCs. After 33 FCs, the advice was strict avoidance, whereof 82% followed a less strict diet. After 16 FCs, the advice was avoidance but products with PAL allowed, whereof 19% followed a less strict and 25% a stricter diet. In 9 FCs with the least strict advice, "(small) amounts allowed'', 67% followed a stricter diet. Three variables were associated with adherence: misremembering dietary advice, impaired health-related quality of life (HRQL) on domain "Emotional impact'' and the need for dietary change after the FC. CONCLUSION: After one third of the positive FCs, patients adhered to the dietary advice. Variables associated with adherence were misremembering dietary advice, impaired HRQL on domain "Emotional impact'' and the need for dietary change after the FC. It seems important that healthcare professionals should more frequently apply adherence-enhancing strategies to improve dietary adherence.

Analysing the protection from respiratory tract infections and allergic diseases early in life by human milk components: the PRIMA birth cohort.

BACKGROUND: Many studies support the protective effect of breastfeeding on respiratory tract infections. Although infant formulas have been developed to provide adequate nutritional solutions, many components in human milk contributing to the protection of newborns and aiding immune development still need to be identified. In this paper we present the methodology of the "Protecting against Respiratory tract lnfections through human Milk Analysis" (PRIMA) cohort, which is an observational, prospective and multi-centre birth cohort aiming to identify novel functions of components in human milk that are protective against respiratory tract infections and allergic diseases early in life. METHODS: For the PRIMA human milk cohort we aim to recruit 1000 mother-child pairs in the first month postpartum. At one week, one, three, and six months after birth, fresh human milk samples will be collected and processed. In order to identify protective components, the level of pathogen specific antibodies, T cell composition, Human milk oligosaccharides, as well as extracellular vesicles (EVs) will be analysed, in the milk samples in relation to clinical data which are collected using two-weekly parental questionnaires. The primary outcome of this study is the number of parent-reported medically attended respiratory infections. Secondary outcomes that will be measured are physician diagnosed (respiratory) infections and allergies during the first year of life. DISCUSSION: The PRIMA human milk cohort will be a large prospective healthy birth cohort in which we will use an integrated, multidisciplinary approach to identify the longitudinal effect human milk components that play a role in preventing (respiratory) infections and allergies during the first year of life. Ultimately, we believe that this study will provide novel insights into immunomodulatory components in human milk. This may allow for optimizing formula feeding for all non-breastfed infants.

Measurement of IgE to hazelnut allergen components cannot replace hazelnut challenge in Dutch adults.

BACKGROUND: Component-resolved diagnostics (CRD) help predict hazelnut allergy (HA) in children, but are of unknown diagnostic value in adults. This study aimed to evaluate the diagnostic accuracy of IgE to hazelnut extract and components in adults. METHODS: A Dutch population of consecutively presenting adults suspected of HA, who underwent a double-blind placebo-controlled food challenge, were included. Serum IgE to hazelnut extract and Cor a 1, 8, 9, and 14 was measured on ImmunoCAP. Diagnostic accuracy was assessed by area under the curve (AUC) analysis. RESULTS: Of 89 patients undergoing challenge, 46 had challenge-confirmed HA: 17 based on objective and 29 based on subjective symptoms. At commonly applied cutoffs 0.1 and 0.35 kUA /L, high sensitivity was observed for IgE to hazelnut extract and Cor a 1 (range 85-91%), and high specificity for IgE to Cor a 8, 9 and 14 (range 77-95%). However, the AUCs for hazelnut extract and components were too low for accurate prediction of HA (range 0.50-0.56). Combining hazelnut extract and component IgE measurements did not significantly improve accuracy. Higher IgE levels to Cor a 9 and 14 were tentatively associated with HA with objective symptoms, but the corresponding AUCs still only reached 0.68 and 0.63, respectively. CONCLUSIONS: Although hazelnut allergic adults are generally sensitized to hazelnut extract and Cor a 1, and hazelnut tolerant adults are usually not sensitized to Cor a 8, 9, or 14, challenge testing is still needed to accurately discriminate between presence and absence of HA in adults from a birch-endemic country.

Development and validation of the food allergy severity score.

BACKGROUND: The heterogeneity and lack of validation of existing severity scores for food allergic reactions limit standardization of case management and research advances. We aimed to develop and validate a severity score for food allergic reactions. METHODS: Following a multidisciplinary experts consensus, it was decided to develop a food allergy severity score (FASS) with ordinal (oFASS) and numerical (nFASS) formats. oFASS with 3 and 5 grades were generated through expert consensus, and nFASS by mathematical modeling. Evaluation was performed in the EuroPrevall outpatient clinic cohort (8232 food reactions) by logistic regression with request of emergency care and medications used as outcomes. Discrimination, classification, and calibration were calculated. Bootstrapping internal validation was followed by external validation (logistic regression) in 5 cohorts (3622 food reactions). Correlation of nFASS with the severity classification done by expert allergy clinicians by Best-Worst Scaling of 32 food reactions was calculated. RESULTS: oFASS and nFASS map consistently, with nFASS having greater granularity. With the outcomes emergency care, adrenaline and critical medical treatment, oFASS and nFASS had a good discrimination (receiver operating characteristic area under the curve [ROC-AUC]>0.80), classification (sensitivity 0.87-0.92, specificity 0.73-0.78), and calibration. Bootstrapping over ROC-AUC showed negligible biases (1.0 × 10-6 -1.23 × 10-3 ). In external validation, nFASS performed best with higher ROC-AUC. nFASS was strongly correlated (R 0.89) to best-worst scoring of 334 expert clinicians. CONCLUSION: FASS is a validated and reliable method to measure severity of food allergic reactions. The ordinal and numerical versions that map onto each other are suitable for use by different stakeholders in different settings.

Diagnostic accuracy of Ara h 2 for detecting peanut allergy in children.

BACKGROUND: Specific IgE to Ara h 2 is a diagnostic test for peanut allergy which may reduce the need for double-blind placebo-controlled food challenges (DBPCFC); however, guidance for using Ara h 2 in place of DBPCFCs has not been validated. OBJECTIVE: To prospectively evaluate 1) diagnostic accuracy of previously published Ara h 2 cut-off levels to diagnose peanut allergy in children and 2) costs. METHODS: A consecutive series of 150 children age 3.5 to 18 years was evaluated in secondary and tertiary settings in the Netherlands. sIgE to Ara h 2 was the index test, and oral peanut ingestion was the reference test. Oral peanut ingestion was home or supervised introduction for Ara h 2 ≤ 0.1, DBPCFC for 0.1-5.0 and open food challenge for ≥5.0. Costs were calculated using financial healthcare data. RESULTS: A conclusive reference test was performed in 113 children (75%). Sixty-four children (57%) had peanut allergy, as confirmed by a DBPCFC (27/47) or an open challenge (37/50). Forty-nine children (43%) were considered peanut-tolerant after peanut introduction (19/19), a DBPCFC (20/47) or an open challenge (10/50). Area under the curve for Ara h 2 was 0.94 (95% CI 0.90-0.98). The diagnostic flow chart correctly classified 26/26 (100%; 84-100) of children with Ara h 2 ≤ 0.1 as peanut-tolerant and 34/35 (97%; 83-100) of children with Ara h 2 ≥ 5.0 as peanut-allergic. At a cut-off of ≤0.1 and ≥5.0, a sensitivity of respectively 100% (93-100) and 53% (38-67) was observed and a specificity of 53% (38-67) and 98% (87-100). Mean annual costs of the flow chart were estimated as €320-€636 per patient lower than following national allergy guidelines. CONCLUSIONS: In this diagnostic accuracy study, which did not take into account pretest probability, we have validated previously published Ara h 2 cut-off levels which are associated with peanut tolerance and allergy.

Predicting the allergenicity of legume proteins using a PBMC gene expression assay.

BACKGROUND: Food proteins differ in their allergenic potential. Currently, there is no predictive and validated bio-assay to evaluate the allergenicity of novel food proteins. The objective of this study was to investigate the potential of a human peripheral blood mononuclear cell (PBMC) gene expression assay to identify biomarkers to predict the allergenicity of legume proteins. RESULTS: PBMCs from healthy donors were exposed to weakly and strongly allergenic legume proteins (2S albumins, and 7S and 11S globulins from white bean, soybean, peanut, pea and lupine) in three experiments. Possible biomarkers for allergenicity were investigated by exposing PBMCs to a protein pair of weakly (white bean) and strongly allergenic (soybean) 7S globulins in a pilot experiment. Gene expression was measured by RNA-sequencing and differentially expressed genes were selected as biomarkers. 153 genes were identified as having significantly different expression levels to the 7S globulin of white bean compared to soybean. Inclusion of multiple protein pairs from 2S albumins (lupine and peanut) and 7S globulins (white bean and soybean) in a larger study, led to the selection of CCL2, CCL7, and RASD2 as biomarkers to distinguish weakly from strongly allergenic proteins. The relevance of these three biomarkers was confirmed by qPCR when PBMCs were exposed to a larger panel of weakly and strongly allergenic legume proteins (2S albumins, and 7S and 11S globulins from white bean, soybean, peanut, pea and lupine). CONCLUSIONS: The PBMC gene expression assay can potentially distinguish weakly from strongly allergenic legume proteins within a protein family, though it will be challenging to develop a generic method for all protein families from plant and animal sources. Graded responses within a protein family might be of more value in allergenicity prediction instead of a yes or no classification.

Ranking of 10 legumes according to the prevalence of sensitization as a parameter to characterize allergenic proteins.

Predicting the allergenicity of novel proteins is challenging due to the absence of validated predictive methods and a well-defined reference set of proteins. The prevalence of sensitization could be a parameter to select reference proteins to characterize allergenic proteins. This study investigated whether the prevalence of sensitization of legume extracts and proteins can indeed be used for this purpose. A random sample of suspected food-allergic patients (n=106) was therefore selected. 10 extracts (processed and non-processed) and 18 individual proteins (2S albumins, 7S and 11S globulins) from black lentil, blue and white lupine, chickpea, faba bean, green lentil, pea, peanut, soybean, and white bean were isolated and the prevalence of sensitization and the intensity of IgE binding were evaluated. The prevalence of sensitization ranged from 5.7 % (faba bean and green lentil) to 14.2 % (peanut). The prevalence of sensitization for individual legume proteins ranged from 0.0 % for albumin 1 (pea) to 15.1 %-17.9 % for Ara h 1, 2, 3, and 6 (peanut). The prevalence of sensitization correlated strongly with the intensity of IgE binding for individual proteins (p < 0.05, ρ = 0.894), for extracts no correlation was found. The discovered ranking can be used to select reference proteins for the development and validation of predictive in vitro or in vivo assays for the assessment of the sensitizing potential.

Digestion and Transport across the Intestinal Epithelium Affects the Allergenicity of Ara h 1 and 3 but Not of Ara h 2 and 6.

SCOPE: No accepted and validated methods are currently available which can accurately predict protein allergenicity. In this study, the role of digestion and transport on protein allergenicity is investigated. METHODS AND RESULTS: Peanut allergens (Ara h 1, 2, 3, and 6) and a milk allergen (ß-lactoglobulin) are transported across pig intestinal epithelium using the InTESTine model and afterward basophil activation is measured to assess the (remaining) functional properties. Additionally, allergens are digested by pepsin prior to epithelial transport and their allergenicity is assessed in a human mast cell activation assay. Remarkably, transported Ara h 1 and 3 are not able to activate basophils, in contrast to Ara h 2 and 6. Digestion prior to transport results in a significant increase in mast cell activation of Ara h 1 and 3 dependent on the length of digestion time. Activation of mast cells by Ara h 2 and 6 is unaffected by digestion prior to transport. CONCLUSIONS: Digestion and transport influences the allergenicity of Ara h 1 and 3, but not of Ara h 2 and 6. The influence of digestion and transport on protein allergenicity may explain why current in vitro assays are not predictive for allergenicity.

Estimating the Risk of Severe Peanut Allergy Using Clinical Background and IgE Sensitization Profiles.

Background: It is not well-understood why symptom severity varies between patients with peanut allergy (PA). Objective: To gain insight into the clinical profile of subjects with mild-to-moderate and severe PA, and investigate individual and collective predictive accuracy of clinical background and IgE to peanut extract and components for PA severity. Methods: Data on demographics, patient history and sensitization at extract and component level of 393 patients with probable PA (symptoms ≤ 2 h + IgE sensitization) from 12 EuroPrevall centers were analyzed. Univariable and penalized multivariable regression analyses were used to evaluate risk factors and biomarkers for severity. Results: Female sex, age at onset of PA, symptoms elicited by skin contact with peanut, family atopy, atopic dermatitis, house dust mite and latex allergy were independently associated with severe PA; birch pollen allergy with mild-to-moderate PA. The cross-validated AUC of all clinical background determinants combined (0.74) was significantly larger than the AUC of tests for sensitization to extract (0.63) or peanut components (0.54-0.64). Although larger skin prick test wheal size, and higher IgE to peanut extract, Ara h 1 and Ara h 2/6, were associated with severe PA, and higher IgE to Ara h 8 with mild-to-moderate PA, addition of these measurements of sensitization to the clinical background model did not significantly improve the AUC. Conclusions: Models combining clinical characteristics and IgE sensitization patterns can help establish the risk of severe reactions for peanut allergic patients, but clinical background determinants are most valuable for predicting severity of probable PA in an individual patient.

Walnut Allergy Across Europe: Distribution of Allergen Sensitization Patterns and Prediction of Severity.

BACKGROUND: Walnut allergy is common across the globe, but data on the involvement of individual walnut components are scarce. OBJECTIVES: To identify geographical differences in walnut component sensitization across Europe, explore cosensitization and cross-reactivity, and assess associations of clinical and serological determinants with severity of walnut allergy. METHODS: As part of the EuroPrevall outpatient surveys in 12 European cities, standardized clinical evaluation was conducted in 531 individuals reporting symptoms to walnut, with sensitization to all known walnut components assessed in 202 subjects. Multivariable Lasso regression was applied to investigate predictors for walnut allergy severity. RESULTS: Birch-pollen-related walnut sensitization (Jug r 5) dominated in Northern and Central Europe and lipid transfer protein sensitization (Jug r 3) in Southern Europe. Profilin sensitization (Jug r 7) was prominent throughout Europe. Sensitization to storage proteins (Jug r 1, 2, 4, and 6) was detected in up to 10% of subjects. The walnut components that showed strong correlations with pollen and other foods differed between centers. The combination of determinants best predicting walnut allergy severity were symptoms upon skin contact with walnut, atopic dermatitis (ever), family history of atopic disease, mugwort pollen allergy, sensitization to cat or dog, positive skin prick test result to walnut, and IgE to Jug r 1, 5, 7, or carbohydrate determinants (area under the curve = 0.81; 95% CI, 0.73-0.89). CONCLUSIONS: Walnut-allergic subjects across Europe show clear geographical differences in walnut component sensitization and cosensitization patterns. A predictive model combining results from component-based serology testing with results from extract-based testing and information on clinical background allows for good discrimination between mild to moderate and severe walnut allergy.

Predicting food allergy: The value of patient history reinforced.

BACKGROUND: EAACI guidelines emphasize the importance of patient history in diagnosing food allergy (FA) and the need for studies investigating its value using standardized allergy-focused questionnaires. OBJECTIVE: To determine the contribution of reaction characteristics, allergic comorbidities and demographics to prediction of FA in individuals experiencing food-related adverse reactions. METHODS: Adult and school-age participants in the standardized EuroPrevall population surveys, with self-reported FA, were included. Penalized multivariable regression was used to assess the association of patient history determinants with "probable" FA, defined as a food-specific case history supported by relevant IgE sensitization. RESULTS: In adults (N = 844), reproducibility of reaction (OR 1.35 [95% CI 1.29-1.41]), oral allergy symptoms (OAS) (4.46 [4.19-4.75]), allergic rhinitis (AR) comorbidity (2.82 [2.68-2.95]), asthma comorbidity (1.38 [1.30-1.46]) and male sex (1.50 [1.41-1.59]) were positively associated with probable FA. Gastrointestinal symptoms (0.88 [0.85-0.91]) made probable FA less likely. The AUC of a model combining all selected predictors was 0.85 after cross-validation. In children (N = 670), OAS (2.26 [2.09-2.44]) and AR comorbidity (1.47 [CI 1.39-1.55]) contributed most to prediction of probable FA, with a combined cross-validation-based AUC of 0.73. When focusing on plant foods, the dominant source of FA in adults, the pediatric model also included gastrointestinal symptoms (inverse association), and the AUC increased to 0.81. CONCLUSIONS: In both adults and school-age children from the general population, reporting of OAS and of AR comorbidity appear to be the strongest predictors of probable FA. Patient history particularly allows for good discrimination between presence and absence of probable plant FA.

Accurate Prediction of Peanut Allergy in One-Third of Adults Using a Validated Ara h 2 Cutoff.

BACKGROUND: The diagnostic value of peanut components is extensively studied in children, but to a lesser extent in adults with suspected peanut allergy. The use of peanut components in daily practice may reduce the need for double-blind placebo-controlled food challenges (DBPCFCs); however, validation studies are currently lacking. OBJECTIVE: To evaluate the diagnostic value of (combined) peanut components and validate a previously found Ara h 2 cutoff level with 100% positive predictive value (PPV) in adults with suspected peanut allergy. METHODS: Adults who underwent a peanut DBPCFC were included: 84 patients from a previous study (2002-2012) and 70 new patients (2012-2019). Specific IgE (sIgE) to peanut extract, Ara h 1, 2, 3, 6, and 8 was measured using ImmunoCAP. Diagnostic value was assessed with an area under the curve (AUC) analysis. RESULTS: In total, 95 (62%) patients were peanut allergic. sIgE to Ara h 2 and Ara h 6 were the best predictors with an AUC (95% confidence interval) of 0.85 (0.79-0.91) and 0.85 (0.79-0.92), respectively. The Ara h 2 cutoff level with 100% PPV (≥1.75 kUA/L) was validated in the 70 new patients. Thirty percent of all included patients could be classified correctly as peanut allergic using this validated cutoff level. CONCLUSION: sIgE to Ara h 2 and Ara h 6 have equally high discriminative ability. Peanut allergy can be predicted accurately in one-third of adults using a validated cutoff level of sIgE to Ara h 2.