Travel Distance to Subspecialty Clinic and Outcomes in Patients with Fibrotic Interstitial Lung Disease.

Rationale: Early access to subspecialty care is associated with improved outcomes for patients with fibrotic interstitial lung disease (ILD). Access to ILD care may be limited for patients living far from subspecialty clinics. Objectives: To test the hypothesis that greater travel distance to access ILD clinical care would be associated with more severe disease at time of referral and worse clinical outcomes. Methods: Patients with fibrotic ILD were recruited from a multicenter national pulmonary fibrosis registry. Residential postal codes were geocoded to estimate travel distance from the home to the clinic. Travel distance was dichotomized at ⩽70 km (near) and >70 km (far). Demographics and disease severity at the initial referral, changes in lung function, and the risk of death or lung transplant were analyzed in unadjusted and adjusted models for their association with travel distance. Results: The cohort included 1,162 patients, of whom 856 lived near to their ILD clinic and 306 lived far from their ILD clinic. Patients residing farther from their clinic were younger, more likely to have smoked, had a greater 6-minute-walk distance, and had lower composite risk scores than patients residing closer to their clinic. In models adjusted for age, sex, and baseline forced vital capacity, patients from farther away had a greater risk of death or lung transplant than patients residing closer (hazard ratio, 1.52; 95% confidence interval [CI], 1.10-2.11), a finding predominantly driven by patients with connective tissue disease-related ILD (hazard ratio, 2.14; 95% CI, 1.16-3.94). Conclusions: Patients with fibrotic ILD with a longer travel distance to their ILD clinic had better prognostic indices at baseline but had a higher risk of death or lung transplant in the total cohort and in patients with connective tissue disease-related ILD. Assuming that disease epidemiology and severity are distributed evenly across geographic regions, these findings raise important questions about equitable access to patient care in large healthcare regions with centralized subspecialty programs.

Predictors of family impact of juvenile localized scleroderma.

OBJECTIVE: To measure the impact juvenile localized scleroderma (jLS) has on family quality of life and to identify predictors of family impact in this population which may inform the development of tailored resources to enhance family functioning for patients with jLS. METHODS: A retrospective cohort study of pediatric patients with jLS and their families was conducted. Five questionnaires were administered at each visit: Pediatric Quality of Life Inventory Family Impact Module (PedsQL-FIM), PedsQL 4.0 Generic Core Scales (PedsQL-Generic), PedsQL Rheumatology Module (PedsQL-RM), Child Health Assessment Questionnaire (CHAQ), and Children's Dermatology Life Quality Index (CDLQI). Linear mixed models with random intercepts for each patient were used to find relationships between family impact scores and clinically relevant variables over time. Variables of interest included disease activity status, methotrexate use, jLS distribution, and scores for PedsQL-Generic and PedsQL-RM. RESULTS: The median baseline PedsQL-FIM total score was 80.9 (IQR = 76.6-97.4). Adjusting for age and sex, the most significant predictors of family impact were PedsQL-Generic scores and four of five PedsQL-RM dimensions (all P < .001); methotrexate use had borderline significance (P = .06). Family impact increased more significantly over time in older patients. In multivariable modeling, PedsQL-Generic total score and jLS "other" distribution were significant for predicting an increased PedsQL-FIM score (P = .003 and P = .03, respectively). CONCLUSIONS: JLS has a moderate family impact. Family impact is predicted by patients' general and disease-specific health-related quality of life (HRQL) and their jLS subtype. There is a trend toward increased family impact with methotrexate treatment. This study emphasizes the importance of family-centered care in jLS.

Characterization of Focal Liver Masses: A Multicenter Comparison of Contrast-Enhanced Ultrasound, Computed Tomography, and Magnetic Resonance Imaging.

OBJECTIVES: To demonstrate the usefulness of contrast-enhanced ultrasound (CEUS) for the evaluation of focal liver masses via a direct comparison to standard ultrasound and computed tomography/magnetic resonance imaging (CT/MRI). METHODS: A cohort of 214 patients with previously undiagnosed focal liver masses were included from 5 different centers. Each patient was imaged using CEUS and CT and/or MRI. Anonymized and randomized images were interpreted by 4 separate blind readers from 3 of the participating centers (2 readers for CEUS and 2 readers for CT/MRI). Readers were blinded to patient demographics and past medical history. Readers were asked to decide if the lesion was benign or malignant, provide a final diagnosis for the lesion, and provide a confidence interval. Results were compared to truth standard from pathology or expert consensus. RESULTS: In determination of malignancy, CEUS had a sensitivity of 95%, specificity of 82%, PPV of 82%, NPV of 95%, statistically better than standard ultrasound (sensitivity 82%, specificity 56%, PPV 60%, NPV 78%) with P < .01 and not statistically different from CT (sensitivity 90%, specificity 73% PPV 81%, NPV 86%) or MRI (sensitivity 85%, specificity 79%, PPV 68%, NPV 91%) with P ≥ .01. In assigning a final diagnosis, CEUS had an accuracy of 78% statistically better than standard ultrasound (46%) with P < .01 and not statistically different from CT (68%) or MRI (71%) with P > .01. CONCLUSIONS: In the evaluation of focal liver lesions, both for determination of malignancy and in accuracy of final diagnosis, CEUS performs better than standard ultrasound and at least equivalent to both CT and MRI.

Epidemiologic and clinical features of chronic hepatitis B virus infection in 8 Canadian provinces: a descriptive study by the Canadian HBV Network.

BACKGROUND: Published Canadian epidemiologic data on hepatitis B virus (HBV) infection include single-centre studies or are focused on Indigenous populations. We performed a study to characterize the demographic and clinical features, liver disease status and treatment of people with chronic hepatitis B in Canada. METHODS: In this descriptive, opportunistic, cross-sectional study, available data for people known to be monoinfected with HBV were collected by the Canadian HBV Network from existing clinical databases, with support from the National Microbiology Laboratory, Public Health Agency of Canada. Data were collected in all provinces with the exception of New Brunswick and Newfoundland and Labrador. We analyzed the data using parametric and nonparametric statistical methods, with a significance level of p < 0.05. RESULTS: In the 9380 unique patient records reviewed, the median age was 48 years, and 5193 patients (55.4%) were male. Ethnicity information was available for 7858 patients, of whom 5803 (73.8%) were Asian, 916 (11.6%) were black and 914 (11.6%) were white. Most of those tested (5556/6796 [81.8%]) were negative for HBV e-antigen, and most of those with fibrosis data (3481/4260 [81.7%]) had minimal liver fibrosis, with more advanced fibrosis noted in older people (> 40 yr). Of the 980 patients with genotype data, 521 (53.2%) had genotype B or C infection. Most of the 9241 patients with known confirmed treatment status received tenofovir disoproxil fumarate (1655 [17.9%]), lamivudine (1434 [15.5%]) or entecavir (548 [5.9%]). INTERPRETATION: Based on available data, Canadian patients with chronic hepatitis B are predominantly Asian and negative for HBV e-antigen, and have genotype B or C infection. Interprovincial variations were noted in antiviral treatment regimen. This multicentre nationwide study provides data regarding patients with chronic hepatitis B and may inform future studies on the epidemiologic features of HBV infection in Canada.

Randomized controlled study of the prediction of diminutive/small colorectal polyp histology using didactic versus computer-based self-learning module in gastroenterology trainees.

BACKGROUND AND AIM: The aim of this randomized trial was to evaluate the performance of self-training versus didactic training in order to increase the diagnostic accuracy of diminutive/small colonic polyp histological prediction by trainees. METHODS: Sixteen trainees reviewed 78 videos (48 iSCAN-OE and 30 NBI) of diminutive/small polyps in a pretraining assessment. Trainees were randomized to receive computer-based self-learning (n = 8) or didactic training (n = 8) using identical teaching materials and videos. The same 78 videos, in a different randomized order, were assessed. The NICE (NBI International Colorectal Endoscopic) and SIMPLE (Simplified Identification Method for Polyp Labeling during Endoscopy) classification systems were used to classify diminutive/small polyps. RESULTS: A higher proportion of high-confidence predictions of polyps was made by the self-training group versus the didactic group using both the SIMPLE classification (77.1% [95% CI 73.4-80.3] vs 69.9% [95% CI 66.1-73.5%] [P = 0.005]) and the NICE classification (77% [95% CI 73.2-80.4%] vs 69.8% [95% CI 66-73.4%] [P = 0.006]). When using NICE, sensitivity of the self-training group compared with the didactic group was 72% versus 83% (P = 0.0005), and the accuracy was 66.1% versus 69.1%. The training improved the confidence of participants and SIMPLE was preferred over NICE. CONCLUSION: Self-learning for the prediction of diminutive/small polyp histology is a method of training that can achieve results similar to didactic training. Availability of adequate self-learning teaching modules could enable widespread implementation of optical diagnosis in clinical practice.

A multimodal (FACILE) classification for optical diagnosis of inflammatory bowel disease associated neoplasia.

BACKGROUND: Characterization of colonic lesions in inflammatory bowel disease (IBD) remains challenging. We developed an endoscopic classification of visual characteristics to identify colitis-associated neoplasia using multimodal advanced endoscopic imaging (Frankfurt Advanced Chromoendoscopic IBD LEsions [FACILE] classification). METHODS: The study was conducted in three phases: 1) development - an expert panel defined endoscopic signs and predictors of dysplasia in IBD and, using multivariable logistic regression created the FACILE classification; 2) validation - using 60 IBD lesions from an image library, two assessments of diagnostic accuracy for neoplasia were performed and interobserver agreement between experts using FACILE was determined; 3) reproducibility - the reproducibility of the FACILE classification was tested in gastroenterologists, trainees, and junior doctors after completion of a training module. RESULTS: The experts initially selected criteria such as morphology, color, surface, vessel architecture, signs of inflammation, and lesion border. Multivariable logistic regression confirmed that nonpolypoid lesion, irregular vessel architecture, irregular surface pattern, and signs of inflammation within the lesion were predictors of dysplasia. Area under the curve of this logistic model using a bootstrapped estimate was 0.76 (0.73 - 0.78). The training module resulted in improved accuracy and kappa agreement in all nonexperts, though in trainees and junior doctors the kappa agreement was still moderate and poor, respectively. CONCLUSION: We developed, validated, and demonstrated reproducibility of a new endoscopic classification (FACILE) for the diagnosis of dysplasia in IBD using all imaging modalities. Flat shape, irregular surface and vascular patterns, and signs of inflammation predicted dysplasia. The diagnostic performance of all nonexpert participants improved after a training module.

Identification of validated case definitions for medical conditions used in primary care electronic medical record databases: a systematic review.

Objectives: Data derived from primary care electronic medical records (EMRs) are being used for research and surveillance. Case definitions are required to identify patients with specific conditions in EMR data with a degree of accuracy. The purpose of this study is to identify and provide a summary of case definitions that have been validated in primary care EMR data. Materials and Methods: We searched MEDLINE and Embase (from inception to June 2016) to identify studies that describe case definitions for clinical conditions in EMR data and report on the performance metrics of these definitions. Results: We identified 40 studies reporting on case definitions for 47 unique clinical conditions. The studies used combinations of International Classification of Disease version 9 (ICD-9) codes, Read codes, laboratory values, and medications in their algorithms. The most common validation metric reported was positive predictive value, with inconsistent reporting of sensitivity and specificity. Discussion: This review describes validated case definitions derived in primary care EMR data, which can be used to understand disease patterns and prevalence among primary care populations. Limitations include incomplete reporting of performance metrics and uncertainty regarding performance of case definitions across different EMR databases and countries. Conclusion: Our review found a significant number of validated case definitions with good performance for use in primary care EMR data. These could be applied to other EMR databases in similar contexts and may enable better disease surveillance when using clinical EMR data. Consistent reporting across validation studies using EMR data would facilitate comparison across studies. Systematic review registration: PROSPERO CRD42016040020 (submitted June 8, 2016, and last revised June 14, 2016).

Development and validation of the SIMPLE endoscopic classification of diminutive and small colorectal polyps.

BACKGROUND: Prediction of histology of small polyps facilitates colonoscopic treatment. The aims of this study were: 1) to develop a simplified polyp classification, 2) to evaluate its performance in predicting polyp histology, and 3) to evaluate the reproducibility of the classification by trainees using multiplatform endoscopic systems. METHODS: In phase 1, a new simplified endoscopic classification for polyps - Simplified Identification Method for Polyp Labeling during Endoscopy (SIMPLE) - was created, using the new I-SCAN OE system (Pentax, Tokyo, Japan), by eight international experts. In phase 2, the accuracy, level of confidence, and interobserver agreement to predict polyp histology before and after training, and univariable/multivariable analysis of the endoscopic features, were performed. In phase 3, the reproducibility of SIMPLE by trainees using different endoscopy platforms was evaluated. RESULTS: Using the SIMPLE classification, the accuracy of experts in predicting polyps was 83 % (95 % confidence interval [CI] 77 % - 88 %) before and 94 % (95 %CI 89 % - 97 %) after training (P â€Š= 0.002). The sensitivity, specificity, positive predictive value, and negative predictive value after training were 97 %, 88 %, 95 %, and 91 %. The interobserver agreement of polyp diagnosis improved from 0.46 (95 %CI 0.30 - 0.64) before to 0.66 (95 %CI 0.48 - 0.82) after training. The trainees demonstrated that the SIMPLE classification is applicable across endoscopy platforms, with similar post-training accuracies for narrow-band imaging NBI classification (0.69; 95 %CI 0.64 - 0.73) and SIMPLE (0.71; 95 %CI 0.67 - 0.75). CONCLUSIONS: Using the I-SCAN OE system, the new SIMPLE classification demonstrated a high degree of accuracy for adenoma diagnosis, meeting the ASGE PIVI recommendations. We demonstrated that SIMPLE may be used with either I-SCAN OE or NBI.

Identification of validated case definitions for chronic disease using electronic medical records: a systematic review protocol.

BACKGROUND: Primary care electronic medical record (EMR) data are being used for research, surveillance, and clinical monitoring. To broaden the reach and usability of EMR data, case definitions must be specified to identify and characterize important chronic conditions. The purpose of this study is to identify all case definitions for a set of chronic conditions that have been tested and validated in primary care EMR and EMR-linked data. This work will provide a reference list of case definitions, together with their performance metrics, and will identify gaps where new case definitions are needed. METHODS: We will consider a set of 40 chronic conditions, previously identified as potentially important for surveillance in a review of multimorbidity measures. We will perform a systematic search of the published literature to identify studies that describe case definitions for clinical conditions in EMR data and report the performance of these definitions. We will stratify our search by studies that use EMR data alone and those that use EMR-linked data. We will compare the performance of different definitions for the same conditions and explore the influence of data source, jurisdiction, and patient population. DISCUSSION: EMR data from primary care providers can be compiled and used for benefit by the healthcare system. Not only does this work have the potential to further develop disease surveillance and health knowledge, EMR surveillance systems can provide rapid feedback to participating physicians regarding their patients. Existing case definitions will serve as a starting point for the development and validation of new case definitions and will enable better surveillance, research, and practice feedback based on detailed clinical EMR data. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42016040020.