Vascular Ehlers-Danlos syndrome (vEDS): CT and histologic findings of pleural and lung parenchymal damage.

OBJECTIVES: To describe CT features of lung involvement in patients with vascular Ehlers-Danlos syndrome (vEDS), a rare genetic condition caused by pathogenic variants within the COL3A1 gene, characterized by recurrent arterial, digestive, and pulmonary events. MATERIAL AND METHODS: All consecutive vEDS patients referred to the national tertiary referral center for vEDS, between 2004 and 2016, were included. Chest CT scans obtained during the initial vascular work-up were reviewed retrospectively by two chest radiologists for lung involvement. Five surgical samples underwent histologic examination. RESULTS: Among 136 enrolled patients (83 women, 53 men; mean age 37 years) with molecularly confirmed vEDS, 24 (17.6%) had a history of respiratory events: 17 with pneumothorax, 4 with hemothorax, and 3 with hemoptysis that required thoracic surgery in 11. CT scans detected lung parenchymal abnormalities in 78 (57.3%) patients: emphysema (mostly centrilobular and paraseptal) in 44 (32.3%), comparable for smokers and non-smokers; clusters of calcified small pulmonary nodules in 9 (6.6%); and cavitated nodules in 4 (2.9%). Histologic examination of surgical samples found arterial abnormalities, emphysema with alveolar ruptures in 3, accompanied by diffuse hemorrhage and increased hemosiderin resorption. CONCLUSION: In vEDS patients, identification of lung parenchymal abnormalities is common on CT. The most frequently observed CT finding was emphysema suggesting alveolar wall rupture which might facilitate the diagnostic screening of the disease in asymptomatic carriers of a genetic COL3A1 gene mutation. The prognostic value and evolution of these parenchymal abnormalities remain to be evaluated. KEY POINTS: • Patients with vEDS can have lung parenchymal changes on top of or next to thoracal vascular abnormalities and that these changes can be present in asymptomatic cases. • The presence of these parenchymal changes is associated with a slightly higher incidence of respiratory events (although not statistically significant). • Identification of the described CT pattern by radiologists and chest physicians may facilitate diagnostic screening.

Accuracy of claim data in the identification and classification of adults with congenital heart diseases in electronic medical records.

BACKGROUND: The content of electronic medical records (EMRs) encompasses both structured data, such as billing codes, and unstructured data, including free-text reports. Epidemiological and clinical research into adult congenital heart disease (ACHD) increasingly relies on administrative claim data using the International Classification of Diseases (9th revision) (ICD-9). In France, administrative databases use ICD-10, the reliability of which is largely unknown in this context. AIMS: To assess the accuracy of ICD-10 codes retrieved from administrative claim data in the identification and classification of ACHD. METHODS: We randomly included 6000 patients hospitalized at least once in 2000-2014 in a cardiology department with a dedicated specialized ACHD Unit. For each patient, the clinical diagnosis extracted from the EMR was compared with the assigned ICD-10 codes. Performance of ICD-10 codes in the identification and classification of ACHD was assessed by estimating sensitivity, specificity and positive predictive value. RESULTS: Among the 6000 patients included, 780 (13%) patients with ACHD were manually identified from EMRs (107,092 documents). ICD-10 codes correctly categorized 629 as having ACHD (sensitivity 0.81, 95% confidence interval 0.78-0.83), with a specificity of 0.99 (95% confidence interval 0.99-1). The performance of ICD-10 codes in correctly categorizing the ACHD defect subtype depended on the defect, with sensitivity ranging from 0 (e.g. unspecified congenital malformation of tricuspid valve) to 1 (e.g. common arterial trunk), and specificity ranging from 0.99 to 1. CONCLUSIONS: Administrative data using ICD-10 codes is a precise tool for detecting ACHD, and may be used to establish a national cohort. Mining free-text reports in addition to coded administrative data may offset the lack of sensitivity and accuracy when describing the spectrum of congenital heart disease using ICD-10 codes.

Development of an Automatic Coding System for Digestive Endoscopies.

Digestive endoscopies, along with all medical procedures in France are coded with the CCAM. This task is done by the physicians, is time-consuming and requires a good knowledge of the terminology besides a medical knowledge. This method offers an automatic coding of endoscopic procedures from free-text reports. Thanks to a supervised learning method, the reports are coded with an average precision and recall of 0.92 on a 1639 texts corpus.

A novel data-driven workflow combining literature and electronic health records to estimate comorbidities burden for a specific disease: a case study on autoimmune comorbidities in patients with celiac disease.

BACKGROUND: Data collected in EHRs have been widely used to identifying specific conditions; however there is still a need for methods to define comorbidities and sources to identify comorbidities burden. We propose an approach to assess comorbidities burden for a specific disease using the literature and EHR data sources in the case of autoimmune diseases in celiac disease (CD). METHODS: We generated a restricted set of comorbidities using the literature (via the MeSH® co-occurrence file). We extracted the 15 most co-occurring autoimmune diseases of the CD. We used mappings of the comorbidities to EHR terminologies: ICD-10 (billing codes), ATC (drugs) and UMLS (clinical reports). Finally, we extracted the concepts from the different data sources. We evaluated our approach using the correlation between prevalence estimates in our cohort and co-occurrence ranking in the literature. RESULTS: We retrieved the comorbidities for 741 patients with CD. 18.1% of patients had at least one of the 15 studied autoimmune disorders. Overall, 79.3% of the mapped concepts were detected only in text, 5.3% only in ICD codes and/or drugs prescriptions, and 15.4% could be found in both sources. Prevalence in our cohort were correlated with literature (Spearman's coefficient 0.789, p = 0.0005). The three most prevalent comorbidities were thyroiditis 12.6% (95% CI 10.1-14.9), type 1 diabetes 2.3% (95% CI 1.2-3.4) and dermatitis herpetiformis 2.0% (95% CI 1.0-3.0). CONCLUSION: We introduced a process that leveraged the MeSH terminology to identify relevant autoimmune comorbidities of the CD and several data sources from EHRs to phenotype a large population of CD patients. We achieved prevalence estimates comparable to the literature.

Induction of resident memory T cells enhances the efficacy of cancer vaccine.

Tissue-resident memory T cells (Trm) represent a new subset of long-lived memory T cells that remain in tissue and do not recirculate. Although they are considered as early immune effectors in infectious diseases, their role in cancer immunosurveillance remains unknown. In a preclinical model of head and neck cancer, we show that intranasal vaccination with a mucosal vector, the B subunit of Shiga toxin, induces local Trm and inhibits tumour growth. As Trm do not recirculate, we demonstrate their crucial role in the efficacy of cancer vaccine with parabiosis experiments. Blockade of TFGß decreases the induction of Trm after mucosal vaccine immunization, resulting in the lower efficacy of cancer vaccine. In order to extrapolate this role of Trm in humans, we show that the number of Trm correlates with a better overall survival in lung cancer in multivariate analysis. The induction of Trm may represent a new surrogate biomarker for the efficacy of cancer vaccine. This study also argues for the development of vaccine strategies designed to elicit them.

Constructing a Pre-Emptive System Based on a Multidimentional Matrix and Autocompletion to Improve Diagnostic Coding in Acute Care Hospitals.

Short-stay MSO (Medicine, Surgery, Obstetrics) hospitalization activities in public and private hospitals providing public services are funded through charges for the services provided (T2A in French). Coding must be well matched to the severity of the patient's condition, to ensure that appropriate funding is provided to the hospital. We propose the use of an autocompletion process and multidimensional matrix, to help physicians to improve the expression of information and to optimize clinical coding. With this approach, physicians without knowledge of the encoding rules begin from a rough concept, which is gradually refined through semantic proximity and uses information on the associated codes stemming of optimized knowledge bases of diagnosis code.

Reviewing 741 patients records in two hours with FASTVISU.

The secondary use of electronic health records opens up new perspectives. They provide researchers with structured data and unstructured data, including free text reports. Many applications been developed to leverage knowledge from free-text reports, but manual review of documents is still a complex process. We developed FASTVISU a web-based application to assist clinicians in reviewing documents. We used FASTVISU to review a set of 6340 documents from 741 patients suffering from the celiac disease. A first automated selection pruned the original set to 847 documents from 276 patients' records. The records were reviewed by two trained physicians to identify the presence of 15 auto-immune diseases. It took respectively two hours and two hours and a half to evaluate the entire corpus. Inter-annotator agreement was high (Cohen's kappa at 0.89). FASTVISU is a user-friendly modular solution to validate entities extracted by NLP methods from free-text documents stored in clinical data warehouses.