Disparities in vaccination rates in solid organ transplant patients.

INTRODUCTION: Vaccinations against preventable respiratory infections such as Streptococcus pneumoniae and influenza are important in immunosuppressed solid organ transplant (SOT) recipients. Little is known about the role of age, race, ethnicity, sex, and sociodemographic factors including rurality, or socioeconomic status (SES) associated with vaccine uptake in this population. METHODS: We conducted a population-based study using the Rochester Epidemiology Project, a medical records linkage system, to assess socioeconomic and demographic factors associated with influenza and pneumococcal vaccination rates among adult recipients of solid organ transplantation (aged 19-64 years) living in four counties in southeastern Minnesota. Vaccination data were obtained from the Minnesota Immunization Information Connection from June 1, 2010 to June 30, 2020. Vaccination rate was assessed with Poisson and logistic regression models. RESULTS: A total of 468 SOT recipients were identified with an overall vaccination rate of 57%-63% for influenza and 56% for pneumococcal vaccines. As expected, vaccination for pneumococcal vaccine positively correlated with influenza vaccination. Rural patients had decreased vaccination in both compared to urban patients, even after adjusting for age, sex, race, ethnicity, and SES. Although the population was mostly White and non-Hispanic, neither vaccination differed by race or ethnicity, but influenza vaccination did by SES. Among organ transplant groups, liver and lung recipients were least vaccinated for influenza, and heart recipients were least up-to-date on pneumococcal vaccines. CONCLUSIONS: Rates of vaccination were below national goals. Rurality was associated with undervaccination. Further investigation is needed to understand and address barriers to vaccination among transplant recipients.

Atopic asthma as a potentially significant but unrecognized risk factor for Kawasaki disease in children.

OBJECTIVES: Childhood asthma is known to be associated with risks of both respiratory and non-respiratory infections. Little is known about the relationship between asthma and the risk of Kawasaki disease (KD). We assessed associations of asthma status and asthma phenotype (e.g. atopic asthma) with KD. METHODS: We performed a population-based retrospective case-control study, using KD cases between January 1, 1979, and December 31, 2016, and two matched controls per case. KD cases were defined by the American Heart Association diagnostic criteria. Asthma status prior to KD (or control) index dates was ascertained by the two asthma criteria, Predetermined Asthma Criteria (PAC) and Asthma Predictive Index (API, a surrogate phenotype of atopic asthma). We assessed whether 4 phenotypes (both PAC + and API+; PAC + only; API + only, and non-asthmatics) were associated with KD. RESULTS: There were 124 KD cases during the study period. The group having both PAC + and API + was significantly associated with the increased odds of KD, compared to non-asthmatics (odds ratio [OR] 4.3; 95% CI: 1.3 - 14.3). While asthma defined by PAC was not associated with KD, asthma defined by PAC positive with eosinophilia (≥4%) was significantly associated with the increased odds of KD (OR: 6.7; 95% CI: 1.6 - 28.6) compared to non-asthmatics. Asthma status defined by API was associated with KD (OR = 4.7; 95% CI: 1.4-15.1). CONCLUSIONS: Atopic asthma may be associated with increased odds of KD. Further prospective studies are needed to determine biological mechanisms underlying the association between atopic asthma and increased odds of KD.

A diagnostic codes-based algorithm improves accuracy for identification of childhood asthma in archival data sets.

OBJECTIVE: While a single but truncated ICD code (493) had been widely used for identifying asthma in asthma care and research, it significantly under-identifies asthma. We aimed to develop and validate a diagnostic codes-based algorithm for identifying asthmatics using Predetermined Asthma Criteria (PAC) as the reference. METHODS: This is a retrospective cross-sectional study which utilized two different coding systems, the Hospital Adaptation of the International Classification of Diseases, Eighth Revision (H-ICDA) and the International Classification of Diseases, Ninth Revision (ICD-9). The algorithm was developed using two population-based asthma study cohorts, and validated in a validation cohort, a random sample of the 1976-2007 Olmsted County Birth Cohort. Performance of the diagnostic codes-based algorithm for ascertaining asthma status against manual chart review for PAC (gold standard) was assessed by determining both criterion and construct validity. RESULTS: Among eligible 267 subjects of the validation cohort, 50% were male, 70% white, and the median age at last follow-up was 17 (interquartile range, 8.7-24.4) years. Asthma prevalence by PAC through manual chart review was 34%. Sensitivity and specificity of the codes-based algorithm for identifying asthma were 82% and 98% respectively. Associations of asthma-related risk factors with asthma status ascertained by the code-based algorithm were similar to those by the manual review. CONCLUSIONS: The diagnostic codes-based algorithm for identifying asthmatics improves accuracy of identification of asthma and can be a useful tool for large scale studies in a setting without automated chart review capabilities.

An Innovative Individual-Level Socioeconomic Measure Predicts Critical Care Outcomes in Older Adults: A Population-Based Study.

BACKGROUND: Little is known about the impact of socioeconomic status (SES) as a key element of social determinants of health on intensive care unit (ICU) outcomes for adults. OBJECTIVE: We assessed whether a validated individual SES index termed HOUSES (HOUsing-based SocioEconomic status index) derived from housing features was associated with short-term outcomes of critical illness including ICU mortality, ICU-free days, hospital-free days, and ICU readmission. METHODS: We performed a population-based cohort study of adult patients living in Olmsted County, Minnesota, admitted to 7 intensive care units at Mayo Clinic from 2011 to 2014. We compared outcomes between the lowest SES group (HOUSES quartile 1 [Q1]) and the higher SES group (HOUSES Q2-4). We stratified the cohort based on age (<50 years old and ≥50 years old). RESULTS: Among 4134 eligible patients, 3378 (82%) patients had SES successfully measured by the HOUSES index. Baseline characteristics, severity of illness, and reason for ICU admission were similar among the different SES groups as measured by HOUSES except for larger number of intoxications and overdoses in younger patients from the lowest SES. In all adult patients, there were no overall differences in mortality, ICU-free days, hospital-free days, or ICU readmissions in patients with higher SES compared to lower SES. Among older patients (>50 years), those with higher SES (HOUSES Q2-4) compared to those with lower SES (HOUSES Q1) had lower mortality rates (hazard ratio = 0.72; 95% CI: 0.56-0.93; adjusted P = .01), increased ICU-free days (mean 1.08 days; 95% CI: 0.34-1.84; adjusted P = .004), and increased hospital-free days (mean 1.20 days; 95% CI: 0.45-1.96; adjusted P = .002). There were no differences in ICU readmission rates (OR = 0.74; 95% CI: 0.55-1.00; P = .051). CONCLUSION: Individual-level SES may be an important determinant or predictor of critical care outcomes in older adults. Housing-based socioeconomic status may be a useful tool for enhancing critical care research and practice.

Identification of asthma control factor in clinical notes using a hybrid deep learning model.

BACKGROUND: There are significant variabilities in guideline-concordant documentation in asthma care. However, assessing clinician's documentation is not feasible using only structured data but requires labor-intensive chart review of electronic health records (EHRs). A certain guideline element in asthma control factors, such as review inhaler techniques, requires context understanding to correctly capture from EHR free text. METHODS: The study data consist of two sets: (1) manual chart reviewed data-1039 clinical notes of 300 patients with asthma diagnosis, and (2) weakly labeled data (distant supervision)-27,363 clinical notes from 800 patients with asthma diagnosis. A context-aware language model, Bidirectional Encoder Representations from Transformers (BERT) was developed to identify inhaler techniques in EHR free text. Both original BERT and clinical BioBERT (cBERT) were applied with a cost-sensitivity to deal with imbalanced data. The distant supervision using weak labels by rules was also incorporated to augment the training set and alleviate a costly manual labeling process in the development of a deep learning algorithm. A hybrid approach using post-hoc rules was also explored to fix BERT model errors. The performance of BERT with/without distant supervision, hybrid, and rule-based models were compared in precision, recall, F-score, and accuracy. RESULTS: The BERT models on the original data performed similar to a rule-based model in F1-score (0.837, 0.845, and 0.838 for rules, BERT, and cBERT, respectively). The BERT models with distant supervision produced higher performance (0.853 and 0.880 for BERT and cBERT, respectively) than without distant supervision and a rule-based model. The hybrid models performed best in F1-score of 0.877 and 0.904 over the distant supervision on BERT and cBERT. CONCLUSIONS: The proposed BERT models with distant supervision demonstrated its capability to identify inhaler techniques in EHR free text, and outperformed both the rule-based model and BERT models trained on the original data. With a distant supervision approach, we may alleviate costly manual chart review to generate the large training data required in most deep learning-based models. A hybrid model was able to fix BERT model errors and further improve the performance.

Establishing an expert consensus for the operational definitions of asthma-associated infectious and inflammatory multimorbidities for computational algorithms through a modified Delphi technique.

BACKGROUND: A subgroup of patients with asthma has been reported to have an increased risk for asthma-associated infectious and inflammatory multimorbidities (AIMs). To systematically investigate the association of asthma with AIMs using a large patient cohort, it is desired to leverage a broad range of electronic health record (EHR) data sources to automatically identify AIMs accurately and efficiently. METHODS: We established an expert consensus for an operational definition for each AIM from EHR through a modified Delphi technique. A series of questions about the operational definition of 19 AIMS (11 infectious diseases and 8 inflammatory diseases) was generated by a core team of experts who considered feasibility, balance between sensitivity and specificity, and generalizability. Eight internal and 5 external expert panelists were invited to individually complete a series of online questionnaires and provide judgement and feedback throughout three sequential internal rounds and two external rounds. Panelists' responses were collected, descriptive statistics tabulated, and results reported back to the entire group. Following each round the core team of experts made iterative edits to the operational definitions until a moderate (≥ 60%) or strong (≥ 80%) level of consensus among the panel was achieved. RESULTS: Response rates for each Delphi round were 100% in all 5 rounds with the achievement of the following consensus levels: (1) Internal panel consensus: 100% for 8 definitions, 88% for 10 definitions, and 75% for 1 definition, (2) External panel consensus: 100% for 12 definitions and 80% for 7 definitions. CONCLUSIONS: The final operational definitions of AIMs established through a modified Delphi technique can serve as a foundation for developing computational algorithms to automatically identify AIMs from EHRs to enable large scale research studies on patient's multimorbidities associated with asthma.

Long-term Incidence of Kawasaki Disease in a North American Community: A Population-Based Study.

To assess the longitudinal incidence of Kawasaki disease (KD) within the well-defined predominantly White population of Olmsted County, MN. This retrospective cohort study used a population-based medical record linkage system and manual chart reviews to identify children with KD in Olmsted County, MN between January 1, 1979-December 31, 2016. Age- and gender-adjusted incidence rates were calculated using the 2010 U.S. White population. 124 children with KD were confirmed during the study period (median age 3.5, 61% male, 85% White, 9% Asian). The overall age- and gender-adjusted incidence rates for all ages and < 5 years old were 9.8 and 21.4 per 100,000 person-years, respectively. There was an overall increase in incidence up to 1994 followed by plateau, except among children between the ages of 1-5 years. There was also an overall increase in incidence among females compared to males. 24% of children had cardiac complications. While the overall incidence of KD in Olmsted County appears to be stable since 1994, the incidence of KD in subgroups of children 1-5 years old and females seems to have increased. Given the rising trends and one-quarter of children developing cardiac complications, further studies identifying factors driving these trends are warranted.

Artificial intelligence approaches using natural language processing to advance EHR-based clinical research.

The wide adoption of electronic health record systems in health care generates big real-world data that open new venues to conduct clinical research. As a large amount of valuable clinical information is locked in clinical narratives, natural language processing techniques as an artificial intelligence approach have been leveraged to extract information from clinical narratives in electronic health records. This capability of natural language processing potentially enables automated chart review for identifying patients with distinctive clinical characteristics in clinical care and reduces methodological heterogeneity in defining phenotype, obscuring biological heterogeneity in research concerning allergy, asthma, and immunology. This brief review discusses the current literature on the secondary use of electronic health record data for clinical research concerning allergy, asthma, and immunology and highlights the potential, challenges, and implications of natural language processing techniques.

Relationship between asthma status and antibody response pattern to 23-valent pneumococcal vaccination.

Objective: Asthma poses an increased risk for serious pneumococcal disease, but little is known about the influence of asthma status on the 23-valent serotype-specific pneumococcal antibody response. We examined differences in antibody titers between pre- and post-vaccination with 23-valent pneumococcal polysaccharide vaccine (PPSV-23) in relation to asthma status. Methods: Asthma status was retrospectively ascertained by the Predetermined Asthma Criteria in an existing vaccine cohort through comprehensive medical record review. Twenty-three serotype-specific pneumococcal antibody titers measured at baseline and 4-6 weeks post-vaccination were analyzed. Vaccine responses to PPSV-23 were calculated from pre- to post-vaccine titers for each of the serotypes. Results: Of the 64 eligible and enrolled subjects, 18 (28%) had asthma. Controls (i.e., subjects without asthma) demonstrated a statistically significant fold change response compared to their baseline for all serotypes, while those with asthma did not mount a significant response to serotypes 7F, 22F, and 23F. The overall vaccine response as measured by fold change over baseline was lower in subjects with asthma than controls. Conclusions: Poorer humoral immune responses to PPSV-23 as measured by fold change were more likely to be observed in subjects with asthma compared to controls. We recommend the consideration of asthma status when interpreting vaccine response for immune competence workup through larger studies. Further studies are warranted to replicate these findings.

Use of Asthma APGAR Tools in Primary Care Practices: A Cluster-Randomized Controlled Trial.

PURPOSE: The purpose of this study was to assess patient and practice outcomes after introducing the Asthma APGAR (Activities, Persistent, triGGers, Asthma medications, Response to therapy) tools into primary care practices. METHODS: We used a pragmatic cluster-randomized controlled design in 18 US family medicine and pediatric practices to compare outcomes in patients with persistent asthma aged 5 to 45 years after introduction of the Asthma APGAR tools vs usual care. Patient outcomes included asthma control, quality of life, and emergency department (ED), urgent care, and inpatient hospital visits. The practice outcome was adherence to asthma guidelines. RESULTS: We enrolled 1,066 patients: 245 children, 174 adolescents, and 647 adults. Sixty-five percent (692 patients) completed both baseline and 12-month questionnaires, allowing analysis for patient-reported outcomes. Electronic health record data were available for 1,063 patients (99.7%) for practice outcomes. The proportion of patients reporting an asthma-related ED, urgent care, or hospital visit in the final 6 months of the study was lower in the APGAR practices vs usual care practices (10.6% vs 20.9%, P = .004). The percentage of patients with "in control" asthma increased more between baseline and 1 year in the APGAR group vs usual care group (13.5% vs 3.4%, P =.0001 vs P =.86) with a trend toward better control scores and asthma-related quality of life in the former at 1 year (P ≤.06 and P = .06, respectively). APGAR practices improved their adherence to 3 or more guideline elements compared with usual care practices (20.7% increase vs 1.9% decrease, P = .001). CONCLUSIONS: Introduction of the Asthma APGAR tools improves rates of asthma control; reduces asthma-related ED, urgent care, and hospital visits; and increases practices' adherence to asthma management guidelines.

Modeling asynchronous event sequences with RNNs.

Sequences of events have often been modeled with computational techniques, but typical preprocessing steps and problem settings do not explicitly address the ramifications of timestamped events. Clinical data, such as is found in electronic health records (EHRs), typically comes with timestamp information. In this work, we define event sequences and their properties: synchronicity, evenness, and co-cardinality; we then show how asynchronous, uneven, and multi-cardinal problem settings can support explicit accountings of relative time. Our evaluation uses the temporally sensitive clinical use case of pediatric asthma, which is a chronic disease with symptoms (and lack thereof) evolving over time. We show several approaches to explicitly incorporating relative time into a recurrent neural network (RNN) model that improve the overall classification of patients into those with no asthma, those with persistent asthma, those in long-term remission, and those who have experienced relapse. We also compare and contrast these results with those in an inpatient intensive care setting.

Application of a Natural Language Processing Algorithm to Asthma Ascertainment. An Automated Chart Review.

RATIONALE: Difficulty of asthma ascertainment and its associated methodologic heterogeneity have created significant barriers to asthma care and research. OBJECTIVES: We evaluated the validity of an existing natural language processing (NLP) algorithm for asthma criteria to enable an automated chart review using electronic medical records (EMRs). METHODS: The study was designed as a retrospective birth cohort study using a random sample of 500 subjects from the 1997-2007 Mayo Birth Cohort who were born at Mayo Clinic and enrolled in primary pediatric care at Mayo Clinic Rochester. Performance of NLP-based asthma ascertainment using predetermined asthma criteria was assessed by determining both criterion validity (chart review of EMRs by abstractor as a gold standard) and construct validity (association with known risk factors for asthma, such as allergic rhinitis). MEASUREMENTS AND MAIN RESULTS: After excluding three subjects whose respiratory symptoms could be attributed to other conditions (e.g., tracheomalacia), among the remaining eligible 497 subjects, 51% were male, 77% white persons, and the median age at last follow-up date was 11.5 years. The asthma prevalence was 31% in the study cohort. Sensitivity, specificity, positive predictive value, and negative predictive value for NLP algorithm in predicting asthma status were 97%, 95%, 90%, and 98%, respectively. The risk factors for asthma (e.g., allergic rhinitis) that were identified either by NLP or the abstractor were the same. CONCLUSIONS: Asthma ascertainment through NLP should be considered in the era of EMRs because it can enable large-scale clinical studies in a more time-efficient manner and improve the recognition and care of childhood asthma in practice.

Automated chart review utilizing natural language processing algorithm for asthma predictive index.

BACKGROUND: Thus far, no algorithms have been developed to automatically extract patients who meet Asthma Predictive Index (API) criteria from the Electronic health records (EHR) yet. Our objective is to develop and validate a natural language processing (NLP) algorithm to identify patients that meet API criteria. METHODS: This is a cross-sectional study nested in a birth cohort study in Olmsted County, MN. Asthma status ascertained by manual chart review based on API criteria served as gold standard. NLP-API was developed on a training cohort (n = 87) and validated on a test cohort (n = 427). Criterion validity was measured by sensitivity, specificity, positive predictive value and negative predictive value of the NLP algorithm against manual chart review for asthma status. Construct validity was determined by associations of asthma status defined by NLP-API with known risk factors for asthma. RESULTS: Among the eligible 427 subjects of the test cohort, 48% were males and 74% were White. Median age was 5.3 years (interquartile range 3.6-6.8). 35 (8%) had a history of asthma by NLP-API vs. 36 (8%) by abstractor with 31 by both approaches. NLP-API predicted asthma status with sensitivity 86%, specificity 98%, positive predictive value 88%, negative predictive value 98%. Asthma status by both NLP and manual chart review were significantly associated with the known asthma risk factors, such as history of allergic rhinitis, eczema, family history of asthma, and maternal history of smoking during pregnancy (p value < 0.05). Maternal smoking [odds ratio: 4.4, 95% confidence interval 1.8-10.7] was associated with asthma status determined by NLP-API and abstractor, and the effect sizes were similar between the reviews with 4.4 vs 4.2 respectively. CONCLUSION: NLP-API was able to ascertain asthma status in children mining from EHR and has a potential to enhance asthma care and research through population management and large-scale studies when identifying children who meet API criteria.

Heterogeneity of asthma and the risk of celiac disease in children.

BACKGROUND: Although human leukocyte antigen (HLA)-DR and HLA-DQ genes and gluten play crucial roles in developing celiac disease (CD), most patients with these risk factors still do not develop CD, which indicates additional unrecognized risk factors. OBJECTIVE: To determine the association between asthma and the risk of CD in children. METHODS: We conducted a population-based retrospective case-control study in children who resided in Olmsted County, Minnesota. We identified children with CD (cases) between January 1, 1997, and December 31, 2014, and compared these with children without CD (controls) (1:2 matching). Asthma status was ascertained by using the predetermined asthma criteria (PAC) and the asthma predictive index (API). Data analysis included conditional logistic regression models and an unsupervised network analysis by using an independent phenome-wide association scan (PheWAS) data set. RESULTS: Although asthma status as determined by using PAC was not associated with the risk of CD (odds ratio [OR] 1.4 [95% confidence interval {CI}, 0.8-2.5]; p = 0.2), asthma status by using the API was significantly associated (OR 2.8 [95% CI, 1.3-6.0]; p = 0.008). A subgroup analysis indicated that children with both asthma as determined by using PAC and a family history of asthma had an increased risk of CD compared with those without asthma (OR 2.28 [95% CI, 1.11-4.67]; p = 0.024). PheWAS data showed a cluster of asthma single nucleotide polymorphisms and patients with CD. CONCLUSION: A subgroup of children with asthma who also had a family history of asthma seemed to be at an increased risk of CD, and, thus, the third factor that underlies the risk of CD might be related to genetic factors for asthma. Heterogeneity of asthma plays a role in determining the risk of asthma-related comorbidity.

Effects of increasing levothyroxine on pregnancy outcomes in women with uncontrolled hypothyroidism.

OBJECTIVE: Uncontrolled hypothyroidism has been associated with an increased risk of adverse pregnancy outcomes. We aimed to assess the effectiveness of increasing levothyroxine (LT4) dose on reducing the risk of adverse outcomes for pregnant women with TSH level greater than the recommended 1st trimester limit. DESIGN, PATIENTS, MEASUREMENTS: We reviewed the electronic medical records of pregnant women evaluated from January 2011 to December 2013, who had history of LT4-treated hypothyroidism and were found to have TSH > 2·5 mIU/l in 1st trimester. Women were divided into two groups: group A - LT4 dose was increased within two weeks from the TSH test, group B - LT4 dose remained stable. We compared the frequency of pregnancy loss (primary outcome) and other prespecified pregnancy-related adverse outcomes between groups. RESULTS: There were 85 women in group A (median TSH: 5·0, interquartile range 3·8-6·8 mIU/l) and 11 women in group B (median TSH: 4·5, interquartile range 3·2-4·9 mIU/l). The groups were not different in baseline clinical and socioeconomic characteristics. The mean interval between TSH test and LT4 dose increase was 4·5 (SD 4·6) days. Pregnancy loss was significantly lower in group A (2/85, 2·4%) vs group B (4/11, 36·4%) (P = 0·001). Other pregnancy-related adverse outcomes were similar between groups. CONCLUSIONS: Increasing LT4 dose for women with uncontrolled hypothyroidism in the 1st trimester of pregnancy was associated with a decreased risk of pregnancy loss. Given the limitations of our study, this association awaits further confirmation from larger studies.

Increasing Incidence and Altered Presentation in a Population-based Study of Pediatric Celiac Disease in North America.

OBJECTIVES: Celiac disease (CD) is a common immune-mediated disorder that affects up to 1% of the general population. Recent reports suggest that the incidence of CD has reached a plateau in many countries. We aim to study the incidence and altered presentation of childhood CD in a well-defined population. METHODS: Using the Rochester Epidemiology Project, we retrospectively reviewed Mayo Clinic and Olmsted Medical Center medical records from January 1994 to December 2014. We identified all CD cases of patients ages 18 years or younger at the time of diagnosis. Incidence rates were calculated by adjusting for age, sex, and calendar year and standardizing to the 2010 US white population. RESULTS: We identified 100 patients with CD. Incidence of CD has increased from 8.1 per 100,000 person-years (2000-2002) to 21.5 per 100,000 person-years (2011-2014). There was an increase in CD prevalence in children from 2010 (0.10%) to 2014 (0.17%). Thirty-four patients (34%) presented with classical CD symptoms, 43 (43%) had nonclassical CD, and 23 (23%) were diagnosed by screening asymptomatic high-risk patients. Thirty-six patients (36%) had complete villous atrophy, 51 (51%) had partial atrophy, and 11 (11%) had increased intraepithelial lymphocytes. Two patients were diagnosed without biopsy. Most patients (67%) had a normal body mass index, 17% were overweight/obese, and only 9% were underweight. CONCLUSIONS: Both incidence and prevalence of CD have continued to increase in children during the past 15 years in Olmsted County, Minnesota. Clinical and pathologic presentations of CD are changing over time (more nonclassical and asymptomatic cases are emerging).

What accounts for the association between late preterm births and risk of asthma?

BACKGROUND: Although results of many studies have indicated an increased risk of asthma in former late preterm (LPT) infants, most of these studies did not fully address covariate imbalance. OBJECTIVE: To compare the cumulative frequency of asthma in a population-based cohort of former LPT infants to that of matched term infants in their early childhood, when accounting for covariate imbalance. METHODS: From a population-based birth cohort of children born 2002-2006 in Olmsted County, Minnesota, we assessed a random sample of LPT (34 to 36 6/7 weeks) and frequency-matched term (37 to 40 6/7 weeks) infants. The subjects were followed-up through 2010 or censored based on the last date of contact, with the asthma status based on predetermined criteria. The Kaplan-Meier method was used to estimate the cumulative incidence of asthma during the study period. Cox models were used to estimate the hazard ratio and 95% confidence interval for the risk of asthma, when adjusting for potential confounders. RESULTS: LPT infants (n = 282) had a higher cumulative frequency of asthma than did term infants (n = 297), 29.9 versus 19.5%, respectively; p = 0.01. After adjusting for covariates associated with the risk of asthma, an LPT birth was not associated with a risk of asthma, whereas maternal smoking during pregnancy was associated with a risk of asthma. CONCLUSION: LPT birth was not independently associated with a risk of asthma and other atopic conditions. Clinicians should make an effort to reduce exposure to smoking during pregnancy as a modifiable risk factor for asthma.

Asthma as a risk factor for zoster in adults: A population-based case-control study.

BACKGROUND: We recently reported an increased risk of herpes zoster (shingles or zoster) in children with asthma, but little is known about whether the same is true for adults with asthma. OBJECTIVE: We determined whether asthma is associated with an increased risk of zoster in adults. METHODS: This study was designed as a population-based case-control study. Zoster cases during the study period were identified among adults (aged ≥50 years) who resided in Olmsted County, Minnesota. We compared the frequency of asthma between zoster cases and birthday- and sex-matched control subjects (1:2 matching) without a history of zoster. Asthma status was ascertained based on predetermined criteria. A conditional logistic regression model was used to assess the association of asthma with risk of zoster. RESULTS: A total of 371 zoster cases and their 742 matched control subjects were enrolled. Of the 371 cases, 246 (66%) were female, 348 (94%) were white, and the mean ± SD age was 66.8 ± 10.7 years. Twenty-three percent (n = 87) of zoster cases had a history of asthma compared with 15% (n = 114) of control subjects. Controlling for pertinent covariates and confounders, there was a significant association between a history of asthma and risk of zoster (adjusted odds ratio, 1.70; 95% CI, 1.20-2.42; P = .003). The population attributable risk percentage for asthma was about 10%. CONCLUSIONS: Asthma is an unrecognized risk factor for zoster in adults. Consideration should be given to immunizing adults with asthma aged more than 50 years as a target group.

A new socioeconomic status measure for vaccine research in children using individual housing data: a population-based case-control study.

BACKGROUND: We recently developed HOUSES, an individual housing-based socioeconomic status (SES) measurement for health disparities research. We assessed whether HOUSES was associated with risk of pertussis and pertussis vaccine up-to-date status in children. METHODS: The study utilized a previous population-based case-control study cohort assembled during the 2004-2005 pertussis outbreak. We collected data on pertussis vaccine status (up-to-date status) at the time of the index date. Using a z-score for housing value, actual square footage, and numbers of bedrooms and bathrooms, HOUSES was formulated in continuous variable and categorized into quartiles. Vaccine up-to-date status was compared among subjects with different SES as measured by HOUSES using a chi-square test and logistic regression models. RESULTS: Of the 391 eligible pediatric subjects (median age of 13.1 years with male sex of 55 %), 363 (93 %) were successfully geocoded to formulate HOUSES index. HOUSES was not associated with the risk of pertussis (p = 0.82). Pertussis vaccine up-to-date statuses were 79, 86, 83, and 94 % for children in the first (the lowest SES), second, third, and fourth quartiles of HOUSES, respectively (p = 0.03). HOUSES as a continuous variable was associated with pertussis vaccine up-to-date status (adjusted OR: 1.15 per increment of one unit of HOUSES, 95 % CI: 1.04-1.27, p = 0.008). CONCLUSION: While HOUSES is not associated with the risk of pertussis, it predicts vaccine up-to-date status among children with different SES. HOUSES may be a useful tool for vaccine delivery research among children.

Asthma and risk of breakthrough varicella infection in children.

BACKGROUND: We recently reported a more rapid waning of vaccine-induced humoral immunity (measles vaccine) in children with asthma. It is unknown if asthma affects susceptibility to vaccine-preventable diseases. OBJECTIVE: To determine whether asthma is associated with an increased risk of vaccine-preventable disease, e.g., breakthrough varicella infection. METHODS: This was a retrospective population-based case-control study that examined cases of breakthrough varicella among children between 2005 and 2011. Children with a diagnosis of breakthrough varicella infection in Olmsted County, Minnesota (infection of >42 days after vaccination) between 2005 and 2011 and two age- and sex-matched controls were enrolled for each case. Asthma status was determined by using predetermined criteria. Conditional logistic regression models were used to calculate matched odds ratios (OR) and their corresponding 95% confidence intervals (CI). RESULTS: Of the 165 cases and their 330 matched controls, 48% were boys and the mean (standard deviation) age at the index date was 6.6 ± 3.5 years for both cases and controls. Of the 330 controls, 80 (24%) had two doses of the varicella vaccine compared with only 23 (14%) of the 165 cases (OR 0.29 [95% CI, 0.14-0.61]; p = 0.001). Children with a history of asthma ever had a higher risk of developing breakthrough varicella compared with those without a history of asthma (adjusted OR 1.63 [95% CI, 1.04-2.55]; p = 0.032) when adjusting for elapsed time since the first varicella vaccination and the number of varicella vaccine doses. CONCLUSIONS: A history of asthma might be an unrecognized risk factor for breakthrough varicella infection. Children with asthma should follow the two-dose varicella vaccine policy.