Asthma in electronic health records: validity and phenotyping

This PhD thesis explores the validation of asthma in electronic health records (EHR) and the characteristics of asthma phenotypes in the UK using CPRD GOLD, HES and ONS data. The absence of a universal case definition, the overlap with other diseases and the incomplete recording of diagnostic markers makes the identification of asthma patients in EHR challenging. Furthermore, asthma phenotypes have previously been established based on cluster analysis in small populations, but their prevalence, treatment and outcomes in the general population have not been investigated. Firstly, I conducted a systematic review to understand how past epidemiological studies have validated asthma recording in EHR, including a critical appraisal and list of test measure values for the selected studies. Secondly, I validated algorithms to reliably ascertain the asthma status of patients in CPRD GOLD. This validation study identified multiple algorithms with PPV greater than 80%. The most practical algorithm (presence of a specific asthma diagnostic code) had a PPV of 86.4 (95% CI:77.4-95.4). Thirdly, I quantified the concomitant occurrence of asthma in COPD patients and vice versa in CPRD GOLD. After detailed case review, concomitant asthma and COPD was concluded in 14.8% of validated asthma patients and in 14.5% of validated COPD patients. However, asthma diagnoses may be unreliable in COPD patients, as over 50% of COPD patients had received an asthma code. Finally, I examined the prevalence, treatment, outcomes and characteristics of established asthma phenotypes in CPRD GOLD. Only a minority of patients (37.3%) were classified into these phenotypes using stringent inclusion criteria. Exacerbation rates/1000PY were lowest for benign asthma (106.8 [95% CI:101.2-112.3]), and highest for obese non-eosinophilic asthma (469.0 [95% CI:451.7-486.2]). In conclusion, this thesis provides information on the validation of asthma diagnoses in EHR and the prevalence, treatment, outcomes of predefined asthma phenotypes in the UK primary care population

Paediatrics: messages from Munich.

The aim of this article is to describe paediatric highlights from the 2014 European Respiratory Society (ERS) International Congress in Munich, Germany. Abstracts from the seven groups of the ERS Paediatric Assembly (Respiratory Physiology and Sleep, Asthma and Allergy, Cystic Fibrosis, Respiratory Infection and Immunology, Neonatology and Paediatric Intensive Care, Respiratory Epidemiology, and Bronchology) are presented in the context of the current literature

Biomedical Literature Mining and Knowledge Discovery of Phenotyping Definitions

Indiana University-Purdue University Indianapolis (IUPUI)Phenotyping definitions are essential in cohort identification when conducting clinical research, but they become an obstacle when they are not readily available. Developing new definitions manually requires expert involvement that is labor-intensive, time-consuming, and unscalable. Moreover, automated approaches rely mostly on electronic health records’ data that suffer from bias, confounding, and incompleteness. Limited efforts established in utilizing text-mining and data-driven approaches to automate extraction and literature-based knowledge discovery of phenotyping definitions and to support their scalability. In this dissertation, we proposed a text-mining pipeline combining rule-based and machine-learning methods to automate retrieval, classification, and extraction of phenotyping definitions’ information from literature. To achieve this, we first developed an annotation guideline with ten dimensions to annotate sentences with evidence of phenotyping definitions' modalities, such as phenotypes and laboratories. Two annotators manually annotated a corpus of sentences (n=3,971) extracted from full-text observational studies’ methods sections (n=86). Percent and Kappa statistics showed high inter-annotator agreement on sentence-level annotations. Second, we constructed two validated text classifiers using our annotated corpora: abstract-level and full-text sentence-level. We applied the abstract-level classifier on a large-scale biomedical literature of over 20 million abstracts published between 1975 and 2018 to classify positive abstracts (n=459,406). After retrieving their full-texts (n=120,868), we extracted sentences from their methods sections and used the full-text sentence-level classifier to extract positive sentences (n=2,745,416). Third, we performed a literature-based discovery utilizing the positively classified sentences. Lexica-based methods were used to recognize medical concepts in these sentences (n=19,423). Co-occurrence and association methods were used to identify and rank phenotype candidates that are associated with a phenotype of interest. We derived 12,616,465 associations from our large-scale corpus. Our literature-based associations and large-scale corpus contribute in building new data-driven phenotyping definitions and expanding existing definitions with minimal expert involvement

Smoking assessment and work ability trends in asthma patients – prospective and retrospective study approach

Smoking increases the risk of asthma and impairs the prognosis of the disease and therapeutic response. Smoking cessation is an essential part of the treatment of asthma. The comprehensive treatment of asthma is also important for the patient’s work ability. The prevalence of asthma has grown, and an increasing number of workers have to cope with the disease in their working lives. The present study aimed to evaluate how reliably asthmatics reported their smoking status and the changes in smoking habits over the last 15 years. We investigated how actively physicians discuss and document patient’s smoking status. The study also examined the development of the work ability score (WAS) in asthma patients to find risk factors for poor development of WAS. This study included two cohorts. The Finnish obstructive airway disease (CAD) cohort included 1,329 asthma patients and 959 chronic obstructive pulmonary disease patients. Their smoking habits, work ability, and general health were followed by questionnaires during 10-years. The register-based cohort included 35,650 patients, whose electronic health records (EHR) were analysed with a combination of rule-and deep learning (ULMFiT)-based algorithms. Only 6% of asthmatics had unreliability in the self-reported smoking data. Pack years can be considered only a rough estimate of the comprehensive consumption of tobacco products. Based on the algorithmic analysis, 61% of asthma patients had documented smoking status, and 55% of current smokers had discussed smoking cessation with the clinician during the two-year follow-up. In the future, smoking cessation care should be activated in hospitals. The performance of the ULMFiT-based classifier was good and showed that deep-learning-based models can create efficient tools for utilising the Finnish EHR. Over 90% of the patients’ WAS remained stable throughout the 10-year study period, but 8% of the patients who had more severe asthma, higher BMI, and multiple comorbidities showed significantly poorer outcomes. To support asthma patients’ work ability, comprehensive treatment of asthma and comorbidities, regular controls, and weight management are needed.Tupakoinnin arviointi ja työkyvyn trendit astmapotilailla – prospektiivinen ja retrospektiivinen lähestymistapa Tupakointi lisää astmariskiä, heikentää sairauden ennustetta ja terapeuttista vastetta. Tupakoinnin lopettaminen on tärkeä osa astman hoitoa. Astman kokonaisvaltainen hoito on oleellista myös potilaan työkyvyn kannalta. Astman esiintyvyys on kasvanut ja yhä useamman täytyy selviytyä sairauden kanssa työelämässä. Tutkimuksen tavoitteena oli selvittää kuinka luotettavasti astmaatikot raportoivat tupakointitietojaan ja mitkä ovat tupakointitottumusten muutokset viimeisten 15 v aikana. Tutkimme myös kuinka aktiivisesti lääkärit keskustelevat tupakoinnista ja dokumentoivat potilaan tupakointistatuksen sairaskertomukseen. Lisäksi tavoitteena oli tutkia työkykypisteiden (WAS) kehitystä astmapotilailla, jotta löydettäisiin riskitekijöitä työkyvyn heikolle kehitykselle. Tutkimus sisälsi kaksi kohorttia. Astman ja keuhkoahtaumataudin yksilöllinen hoito -tutkimuskohortti (AST) koostui 1329 astma- ja 959 keuhkoahtauma-tautipotilaasta. Heidän tupakointitapojaan, työkykyään ja yleistä terveyttään seurattiin 10 vuoden ajan kyselylomakkeiden avulla. Rekisteripohjainen kohortti koostui 35 650 aikuispotilaasta, joiden sairauskertomustekstejä analysoitiin sääntöpohjaisten ja syväoppimiseen (ULMFiT) perustuvien algoritmien avulla. Vain 6%:lla astmapotilaista itseraportoidut tupakkatiedot olivat epäluotettavia. Askivuosia voidaan käyttää vain karkeana arviona tupakointitaakasta. Algoritmisten analyysien pohjalta 61%:lla astmapotilaista oli tupakointistatus merkittynä sairauskertomukseen ja 55% nykyisistä tupakoitsijoista oli keskustellut lopetta-misesta lääkärin kanssa. Tulevaisuudessa tupakka- ja nikotiiniriippuvuuden hoitoa tulee aktivoida sairaaloissa. ULMFiT:iin perustuvan tupakointiluokittelijan toimivuus oli hyvä ja osoitti, että syväoppimiseen perustuvat mallit voivat luoda tehokkaita työkaluja suomalaisen sairauskertomuksen hyödyntämiseen. Yli 90%:lla potilaista työkykypistemäärä pysyi vakaana 10 vuoden seuranta-ajan, mutta 8%:lla potilaista, joilla oli vaikeampi astma ja enemmän oheissairauksia, tulokset olivat selkeästi heikommat. Astmapotilaiden työkyvyn tukemiseksi tarvitaan astman ja oheissairauksien kokonaisvaltaista hoitoa sekä ohjausta painonhallinnan

Probiotic interventions in infancy: Benefit and Safety Assessment of Extended Applications

Immaturity of the gut barrier system in the newborn has been seen to underlie a number of chronic diseases originating in infancy and manifesting later in life. The gut microbiota and breast milk provide the most important maturing signals for the gut-related immune system and reinforcement of the gut mucosal barrier function. Recently, the composition of the gut microbiota has been proposed to be instrumental in control of host body weight and metabolism as well as the inflammatory state characterizing overweight and obesity. On this basis, inflammatory Western lifestyle diseases, including overweight development, may represent a potential target for probiotic interventions beyond the well documented clinical applications. The purpose of the present undertaking was to study the efficacy and safety of perinatal probiotic intervention. The material comprised two ongoing, prospective, double-blind NAMI (Nutrition, Allergy, Mucosal immunology and Intestinal microbiota) probiotic interventions. In the mother-infant nutrition and probiotic study altogether 256 women were randomized at their first trimester of pregnancy into a dietary intervention and a control group. The intervention group received intensive dietary counselling provided by a nutritionist, and were further randomized at baseline, double-blind, to receive probiotics (Lactobacillus rhamnosus GG and Bifidobacterium lactis) or placebo. The intervention period extended from the first trimester of pregnancy to the end of exclusive breastfeeding. In the allergy prevention study altogether 159 women were randomized, double-blind, to receive probiotics (Lactobacillus rhamnosus GG) or placebo 4 weeks before expected delivery, the intervention extending for 6 months postnatally. Additionally, patient data on all premature infants with very low birth weight (VLBW) treated in the Department of Paediatrics, Turku University Hospital, during the years 1997 - 2008 were utilized. The perinatal probiotic intervention reduced the risk of gestational diabetes mellitus (GDM) in the mothers and perinatal dietary counselling reduced that of fetal overgrowth in GDM-affected pregnancies. Early gut microbiota modulation with probiotics modified the growth pattern of the child by restraining excessive weight gain during the first years of life. The colostrum adiponectin concentration was demonstrated to be dependent on maternal diet and nutritional status during pregnancy. It was also higher in the colostrum received by normal-weight compared to overweight children at the age of 10 years. The early perinatal probiotic intervention and the postnatal probiotic intervention in VLBW infants were shown to be safe. To conclude, the findings in this study provided clinical evidence supporting the involvement of the initial microbial and nutritional environment in metabolic programming of the child. The manipulation of early gut microbial communities with probiotics might offer an applicable strategy to impact individual energy homeostasis and thus to prevent excessive body-weight gain. The results add weight to the hypothesis that interventions aiming to prevent obesity and its metabolic consequences later in life should be initiated as early as during the perinatal period.Siirretty Doriast

Identifying Clinical Phenotypes of Type 1 Diabetes for the Co-Optimization of Weight and Glycemic Control

Obesity is an increasing concern in the clinical care of youth with type 1 diabetes (T1D). Standard approaches to co-optimize weight and glycemic control are challenged by profound population-level heterogeneity. Therefore, the goal of the dissertation was to apply novel analytic methods to understand heterogeneity in the co-occurrence of weight, glycemia, and underlying patterns of minute-to-minute dysglycemia among youth with T1D. Data from the SEARCH for Diabetes in Youth study were used to characterize subgroups of youth with T1D showing similar weight status and level of glycemic control as distinct ‘weight-glycemia phenotypes’ of T1D. Cross-sectional weight-glycemia phenotypes were identified at the 5+ year follow-up visit (n=1,817) using hierarchical clustering on five measures summarizing the joint distribution of body mass index z-score (BMIz) and hemoglobin A1c (HbA1c), generated by reinforcement learning tree predictions. Longitudinal weight-glycemia phenotypes spanning eight years were identified with longitudinal k-means clustering using baseline and follow-up BMIz and HbA1c measures (n=570). Logistic regression modeling tested for differences in the emergence of early/subclinical diabetes complications across subgroups. Seven-day blinded continuous glucose monitoring (CGM) data from baseline of the Flexible Lifestyles Empowering Change randomized trial (n=234, 13-16 years, HbA1c 8-13%) was clustered with a neural network approach to identify subgroups of adolescents with T1D and elevated HbA1c sharing patterns in their CGM data as ‘dysglycemia phenotypes.’ We identified six cross-sectional weight-glycemia phenotypes, including four normal-weight, one overweight, and one subgroup with obesity. Subgroups showed striking differences in other sociodemographic and clinical characteristics suggesting underlying health inequity. We identified four longitudinal weight-glycemia phenotypes associated with different patterns of early/subclinical complications, providing evidence that exposure to co-occurring obesity and worsening glycemic control may accelerate the development and increase the burden of co-morbid complications. We identified three dysglycemia phenotypes with significantly different patterns in hypoglycemia, hyperglycemia, glycemic variability, and 18-month changes in HbA1c. Patient-level drivers of the dysglycemia phenotypes appear to be different from risk factors for poor glycemic control as measured by HbA1c. These studies provide pragmatic, clinically-relevant examples of how novel statistics may be applied to data from T1D to derive patient subgroups for tailored interventions to improve weight alongside glycemic control.Doctor of Philosoph

Gut microbiome westernization in Hmong and Karen refugees and immigrants in the United States

University of Minnesota Ph.D. dissertation. August 2018. Major: Biomedical Informatics and Computational Biology. Advisor: Dan Knights. 1 computer file (PDF); x, 132 pages.Many United States immigrant populations develop metabolic diseases post-immigration, but the causes are not well understood. Although the microbiome plays a role in metabolic disease, there have been no studies measuring the effects of U.S. immigration on the gut microbiome. We collected stool, dietary recalls, and anthropometrics from 514 Hmong and Karen individuals living in Thailand and the U.S., including first- and second-generation immigrants and 19 Karen individuals sampled before and after immigration, as well as from 36 U.S.-born Caucasian individuals. Using 16S and deep shotgun metagenomic DNA sequencing, we found that migration from a non-Western country to the U.S. is associated with immediate loss of gut microbiome diversity and function, with U.S.-associated strains and functions displacing native strains and functions. These effects increase with duration of U.S. residence, and are compounded by obesity and across generations

Allergic Diseases

The present Edition "Allergic diseases - highlights in the clinic, mechanisms and treatment" aims to present some recent aspects related to one of the most prevalent daily clinical expression disease. The effort of a group of outstanding experts from many countries reflects a set of scientific studies very promising for a better clinical care and also to the treatment and control of the allergy. This book provides a valuable reference text in several topics of the clinical allergy and basic issues related to the immune system response. The inflammatory reaction understanding in allergic disease is clearly evidenced, as well as new strategies for further researches