A US-Based Multicenter Retrospective Report of Perioperative Anaphylaxis, 2010-2021.

BACKGROUND: US-based perioperative anaphylaxis (POA) studies are limited to single-center experiences. A recent report found that a serum acute tryptase (sAT) >9.8 ng/mL or mast cell activation (MCA) can predict POA causal agent identification. Urinary mast cell mediator metabolites (uMC) have not been studied in POA. OBJECTIVE: To analyze the epidemiologic data of POA, to determine if sAT or MCA can predict suspected causal agent identification, and to evaluate uMC utility in POA. METHODS: This study is a retrospective multicenter review of POA cases that were subcategorized by suspected causal agent identification status. sAT, MCA (defined as sAT >2 + 1.2 × serum baseline tryptase), and uMC (N-methylhistamine [N-MH], 11ß-prostaglandin-F2α [11ß-PGF2α], leukotriene E4 [LTE4]) were recorded. RESULTS: Of 100 patients (mean age 52 [standard deviation 17] years, 94% adult, 50% female, 90% White, and 2% Hispanic) with POA, 73% had an sAT available, 41% had MCA, 16% had uMC available, and 50% had an identifiable suspected cause. POA cases with an identifiable suspected cause had a positive MCA status (100% vs 78%; P = .01) compared with POA with an unidentifiable cause. An elevated median sAT did not predict causal agent identification. Positive uMC were not associated with suspected causal agent identification during POA. Patients with positive uMC had a higher median sAT (30 vs 6.45 ng/mL; P = .001) and MCA status (96% vs 12%; P = .001) compared with negative uMC patients. Patients with POA had an elevated acute/baseline uMC ratios: 11ß-PGF2α ratio > 1.6, N-MH ratio >1.7, and LTE4 ratio >1.8. CONCLUSIONS: The presence of MCA in POA is associated with suspected causal agent identification. Positive uMC possibly correlate with a higher sAT level and MCA status but require further study. The authors suggest applying an acute/baseline uMC ratio (11ß-PGF2α ratio >1.6, N-MH ratio >1.7, and LTE4 ratio >1.87) in patients with POA for MCA when a tryptase level is inconclusive during POA evaluations.

Predicting Penicillin Allergy: A United States Multicenter Retrospective Study.

BACKGROUND: Using the reaction history in logistic regression and machine learning (ML) models to predict penicillin allergy has been reported based on non-US data. OBJECTIVE: We developed ML positive penicillin allergy testing prediction models from multisite US data. METHODS: Retrospective data from 4 US-based hospitals were grouped into 4 datasets: enriched training (1:3 case-control matched cohort), enriched testing, nonenriched internal testing, and nonenriched external testing. ML algorithms were used for model development. We determined area under the curve (AUC) and applied the Shapley Additive exPlanations (SHAP) framework to interpret risk drivers. RESULTS: Of 4777 patients (mean age 60 [standard deviation: 17] years; 68% women, 91% White, and 86% non-Hispanic) evaluated for penicillin allergy labels, 513 (11%) had positive penicillin allergy testing. Model input variables were frequently missing: immediate or delayed onset (71%), signs or symptoms (13%), and treatment (31%). The gradient-boosted model was the strongest model with an AUC of 0.67 (95% confidence interval [CI]: 0.57-0.77), which improved to 0.87 (95% CI: 0.73-1) when only cases with complete data were used. Top SHAP drivers for positive testing were reactions within the last year and reactions requiring medical attention; female sex and reaction of hives/urticaria were also positive drivers. CONCLUSIONS: An ML prediction model for positive penicillin allergy skin testing using US-based retrospective data did not achieve performance strong enough for acceptance and adoption. The optimal ML prediction model for positive penicillin allergy testing was driven by time since reaction, seek medical attention, female sex, and hives/urticaria.

Improving routine prenatal penicillin allergy testing for reported penicillin allergy.

BACKGROUND: Patients with self-reported antibiotic allergies have a higher cost of care, more frequent infections with resistant bacteria and worse health outcomes than patients without antibiotic allergies. Ultimately, less than 5% of patients who report a penicillin allergy have a clinically significant immune-mediated hypersensitivity reaction when tested. As 10%-30% of the population of pregnant patients are colonised for group B Streptococcus (GBS) and guidelines recommend penicillin as the treatment of choice for GBS, current recommendations support penicillin allergy testing in pregnant patients who report an allergy. METHODS AND INTERVENTION: In this quality improvement project, nursing staff used an algorithm outlining inclusion and exclusion criteria to determine which patients were eligible to have penicillin allergy testing completed. Penicillin allergy testing consisted of a skin test using benzylpenicilloyl polylysine (Pre-Pen), penicillin G potassium, amoxicillin and alkaline hydrolysis mix (penicilloate) as a prick skin test, followed by intradermal skin test and finally an oral challenge with either amoxicillin or penicillin. Patient outcomes were analysed to evaluate the impact of the intervention. RESULTS: Of the 1266 patients receiving prenatal care during the intervention, 236 (19%) reported a history of penicillin allergy, and 212 if these were eligible for testing. 150 of the eligible patients were offered penicillin allergy testing. 101 patients (67%) completed testing and 49 (33%) declined testing. Seven patients (7%) had positive penicillin allergy testing, while 94 patients (93%) had negative penicillin allergy testing and were immediately de-labelled as penicillin allergic. Seventeen of the de-labelled patients subsequently tested positive for GBS colonisation, and all received intrapartum penicillin without adverse events. CONCLUSIONS: Pursuing penicillin allergy testing for pregnant patients with reported penicillin allergy is a safe and feasible approach, allowing for allergy de-labelling and safe, guideline-driven antimicrobial therapy during subsequent labour and delivery hospitalisations. Cost-effectiveness of the allergy testing and impact on later episodes of care should be further investigated.

Autoimmune progesterone dermatitis: a retrospective case series.

Autoimmune progesterone dermatitis (APD) is a rare hypersensitivity disorder characterized by recurring dermatologic manifestations during the luteal phase of the menstrual cycle in women. Well-defined clinical and diagnostic criteria, outcomes measurements, and standard treatments are lacking. Methods: We performed a single-institution retrospective review of adult patients (older than 20 years at the time of diagnosis) with APD. Results: Fourteen patients were included with mean age of clinical onset of 34.3 ± 7.7 (range 24-54) years. There was a delay of 3.9 ± 5.5 (range 0.4-20) years between the onset of disease symptoms and diagnosis. The onset of APD was after exposure to exogenous progesterone in 9 of 14 patients. Progesterone skin test was performed in 9 patients and 6 were positive. Patients frequently presented with urticaria (9/14, 64.3%) and dermatitis (4/14, 28.6%). Continuous combined oral contraceptives (4/14, 28.6%), gonadotropin-releasing hormone agonist (3/14, 21.4%), and hysterectomy with bilateral salpingo-oophorectomy (2/14, 14.3%) were the most common attempted treatments with reliable outcomes. Conclusions: APD is a rare disorder which lacks universal diagnostic measures and criteria, contributing to a significant delay in diagnosis. Large-scale multicenter studies are needed to develop accurate tests, establish diagnostic criteria, and define treatment outcomes.

Risk of pneumonia in asthmatic children using inhaled corticosteroids: a nested case-control study in a birth cohort.

BACKGROUND: Inhaled corticosteroids (ICSs) are important in asthma management, but there are concerns regarding associated risk of pneumonia. While studies in asthmatic adults have shown inconsistent results, this risk in asthmatic children is unclear. OBJECTIVE: Our aim was to determine the association of ICS use with pneumonia risk in asthmatic children. METHODS: A nested case-control study was performed in the Mayo Clinic Birth Cohort. Asthmatic children (<18 years) with a physician diagnosis of asthma were identified from electronic medical records of children born at Mayo Clinic from 1997 to 2016 and followed until 31 December 2017. Pneumonia cases defined by Infectious Disease Society of America were 1:1 matched with controls without pneumonia by age, sex and asthma index date. Exposure was defined as ICS prescription at least 90 days prior to pneumonia. Associations of ICS use, type and dose (low, medium and high) with pneumonia risk were analysed using conditional logistic regression. RESULTS: Of the 2108 asthmatic children eligible for the study (70% mild intermittent and 30% persistent asthma), 312 children developed pneumonia during the study period. ICS use overall was not associated with risk of pneumonia (adjusted OR: 0.94, 95% CI: 0.62 to 1.41). Poorly controlled asthma was significantly associated with the risk of pneumonia (OR: 2.03, 95% CI: 1.35 to 3.05; p<0.001). No ICS type or dose was associated with risk of pneumonia. CONCLUSION: ICS use in asthmatic children was not associated with risk of pneumonia but poorly controlled asthma was. Future asthma studies may need to include pneumonia as a potential outcome of asthma management.

Female sex as a risk factor for penicillin drug allergy in the inpatient setting.

Background: Penicillin is the most common reported drug allergy. Previous literature suggests that there is increased prevalence of penicillin drug allergy in female patients in the outpatient setting. However, this is poorly described in the inpatient setting. Objective: This study was performed to determine whether female sex is an independent risk factor for penicillin allergy in the inpatient setting. Methods: A retrospective review of electronic medical records (January 1, 2001-December 31, 2017) was performed for patients with a history of penicillin allergy who underwent penicillin skin testing (PST). Each chart review included the age at initial skin testing, sex, medications, and medical co-morbidities. The study was approved by the institutional review board. Results: 30,883 patients underwent PST with 29,354 and 1,529 occurring in the outpatient and inpatient setting respectively. 170 patients tested positive with a ≥ 5x5 wheal. Of the 170 positive patients, 122 were female (72%) and 48 were male (28%). 15 patients tested positive in the inpatient setting. Of the 1506 adult patients tested in the inpatient setting, 809 were female and 697 were male. 12 females (92.3%) and 1 one male (7.7%) tested positive with a ≥ 5x5 wheal (OR-10.5; 95% CI-1.4-80.8; p-value=0.02). 23 pediatric patients were tested in the inpatient setting. Two pediatric male patients were positive and no female pediatric patients tested positive (OR-1.7; 95% CI-0.5-5.9; p-value=0.5). Conclusion: In the inpatient setting, adult females are 10 times more likely to have a positive PST compared to males. Female sex may be a potential risk factor for objective penicillin drug allergy in the inpatient setting.

Artificial Intelligence Assesses Clinicians' Adherence to Asthma Guidelines Using Electronic Health Records.

BACKGROUND: Clinicians' asthma guideline adherence in asthma care is suboptimal. The effort to improve adherence can be enhanced by assessing and monitoring clinicians' adherence to guidelines reflected in electronic health records (EHRs), which require costly manual chart review because many care elements cannot be identified by structured data. OBJECTIVE: This study was designed to demonstrate the feasibility of an artificial intelligence tool using natural language processing (NLP) leveraging the free text EHRs of pediatric patients to extract key components of the 2007 National Asthma Education and Prevention Program guidelines. METHODS: This is a retrospective cross-sectional study using a birth cohort with a diagnosis of asthma at Mayo Clinic between 2003 and 2016. We used 1,039 clinical notes with an asthma diagnosis from a random sample of 300 patients. Rule-based NLP algorithms were developed to identify asthma guideline-congruent elements by examining care description in EHR free text. RESULTS: Natural language processing algorithms demonstrated a sensitivity (0.82-1.0), specificity (0.95-1.0), positive predictive value (0.86-1.0), and negative predictive value (0.92-1.0) against manual chart review for asthma guideline-congruent elements. Assessing medication compliance and inhaler technique assessment were the most challenging elements to assess because of the complexity and wide variety of descriptions. CONCLUSIONS: Natural language processing technologies may enable the automated assessment of clinicians' documentation in EHRs regarding adherence to asthma guidelines and can be a useful population management and research tool to assess and monitor asthma care quality. Multisite studies with a larger sample size are needed to assess the generalizability of these NLP algorithms.

Utility and futility of skin testing to address concerns surrounding messenger RNA coronavirus disease 2019 vaccine reactions.

BACKGROUND: The mechanism of coronavirus disease 2019 (COVID-19) vaccine hypersensitivity reactions is unknown. COVID-19 vaccine excipient skin testing has been used in evaluation of these reactions, but its utility in predicting subsequent COVID-19 vaccine tolerance is also unknown. OBJECTIVE: To evaluate the utility of COVID-19 vaccine and vaccine excipient skin testing in both patients with an allergic reaction to their first messenger RNA COVID-19 vaccine dose and patients with a history of polyethylene glycol allergy who have not yet received a COVID-19 vaccine dose. METHODS: In this multicenter, retrospective review, COVID-19 vaccine and vaccine excipient skin testing was performed in patients referred to 1 of 3 large tertiary academic institutions. Patient medical records were reviewed after skin testing to determine subsequent COVID-19 vaccine tolerance. RESULTS: A total of 129 patients underwent skin testing, in whom 12 patients (9.3%) had positive results. There were 101 patients who received a COVID-19 vaccine after the skin testing, which was tolerated in 90 patients (89.1%) with no allergic symptoms, including 5 of 6 patients with positive skin testing results who received a COVID-19 vaccine after the skin testing. The remaining 11 patients experienced minor allergic symptoms after COVID-19 vaccination, none of whom required treatment beyond antihistamines. CONCLUSION: The low positivity rate of COVID-19 vaccine excipient skin testing and high rate of subsequent COVID-19 vaccine tolerance suggest a low utility of this method in evaluation of COVID-19 vaccine hypersensitivity reactions. Focus should shift to the use of existing vaccine allergy practice parameters, with consideration of graded dosing when necessary. On the basis of these results, strict avoidance of subsequent COVID-19 vaccination should be discouraged.

Risk, Mechanisms and Implications of Asthma-Associated Infectious and Inflammatory Multimorbidities (AIMs) among Individuals With Asthma: a Systematic Review and a Case Study.

Our prior work and the work of others have demonstrated that asthma increases the risk of a broad range of both respiratory (e.g., pneumonia and pertussis) and non-respiratory (e.g., zoster and appendicitis) infectious diseases as well as inflammatory diseases (e.g., celiac disease and myocardial infarction [MI]), suggesting the systemic disease nature of asthma and its impact beyond the airways. We call these conditions asthma-associated infectious and inflammatory multimorbidities (AIMs). At present, little is known about why some people with asthma are at high-risk of AIMs, and others are not, to the extent to which controlling asthma reduces the risk of AIMs and which specific therapies mitigate the risk of AIMs. These questions represent a significant knowledge gap in asthma research and unmet needs in asthma care, because there are no guidelines addressing the identification and management of AIMs. This is a systematic review on the association of asthma with the risk of AIMs and a case study to highlight that 1) AIMs are relatively under-recognized conditions, but pose major health threats to people with asthma; 2) AIMs provide insights into immunological and clinical features of asthma as a systemic inflammatory disease beyond a solely chronic airway disease; and 3) it is time to recognize AIMs as a distinctive asthma phenotype in order to advance asthma research and improve asthma care. An improved understanding of AIMs and their underlying mechanisms will bring valuable and new perspectives improving the practice, research, and public health related to asthma.

Artificial intelligence-assisted clinical decision support for childhood asthma management: A randomized clinical trial.

RATIONALE: Clinical decision support (CDS) tools leveraging electronic health records (EHRs) have been an approach for addressing challenges in asthma care but remain under-studied through clinical trials. OBJECTIVES: To assess the effectiveness and efficiency of Asthma-Guidance and Prediction System (A-GPS), an Artificial Intelligence (AI)-assisted CDS tool, in optimizing asthma management through a randomized clinical trial (RCT). METHODS: This was a single-center pragmatic RCT with a stratified randomization design conducted for one year in the primary care pediatric practice of the Mayo Clinic, MN. Children (<18 years) diagnosed with asthma receiving care at the study site were enrolled along with their 42 primary care providers. Study subjects were stratified into three strata (based on asthma severity, asthma care status, and asthma diagnosis) and were blinded to the assigned groups. MEASUREMENTS: Intervention was a quarterly A-GPS report to clinicians including relevant clinical information for asthma management from EHRs and machine learning-based prediction for risk of asthma exacerbation (AE). Primary endpoint was the occurrence of AE within 1 year and secondary outcomes included time required for clinicians to review EHRs for asthma management. MAIN RESULTS: Out of 555 participants invited to the study, 184 consented for the study and were randomized (90 in intervention and 94 in control group). Median age of 184 participants was 8.5 years. While the proportion of children with AE in both groups decreased from the baseline (P = 0.042), there was no difference in AE frequency between the two groups (12% for the intervention group vs. 15% for the control group, Odds Ratio: 0.82; 95%CI 0.374-1.96; P = 0.626) during the study period. For the secondary end points, A-GPS intervention, however, significantly reduced time for reviewing EHRs for asthma management of each participant (median: 3.5 min, IQR: 2-5), compared to usual care without A-GPS (median: 11.3 min, IQR: 6.3-15); p<0.001). Mean health care costs with 95%CI of children during the trial (compared to before the trial) in the intervention group were lower than those in the control group (-$1,036 [-$2177, $44] for the intervention group vs. +$80 [-$841, $1000] for the control group), though there was no significant difference (p = 0.12). Among those who experienced the first AE during the study period (n = 25), those in the intervention group had timelier follow up by the clinical care team compared to those in the control group but no significant difference was found (HR = 1.93; 95% CI: 0.82-1.45, P = 0.10). There was no difference in the proportion of duration when patients had well-controlled asthma during the study period between the intervention and the control groups. CONCLUSIONS: While A-GPS-based intervention showed similar reduction in AE events to usual care, it might reduce clinicians' burden for EHRs review resulting in efficient asthma management. A larger RCT is needed for further studying the findings. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02865967.