Structural validity of the Finnish Manchester-Oxford Foot Questionnaire (MOXFQ) using the Rasch model

Background: The 16-item patient-reported Manchester-Oxford Foot Questionnaire (MOXFQ) with subscales of pain, social interactions, and walking/standing has been claimed for strongest scientific evidence in measuring foot and ankle complaints. This study tests the validity of the Finnish MOXFQ for orthopaedic foot and ankle population using the Rasch analysis. Methods: We translated the MOXFQ into Finnish and used that translation in our study. MOXFQ scores were obtained from 183 patients. Response category distribution, item fit, coverage, targeting, item dependency, ability to measure latent trait (unidimensionality), internal consistency (Cronbach's alpha), and person separation index (PSI) were analyzed. Results: Fifteen of the items had ordered response categories and/or sufficient fit statistics. The subscales provided coverage and targeting. Some residual correlation was noted. Removing one item in the pain subscale led to a unidimensional structure. Alphas and PSIs ranged between 0.68-0.90 and 0.67-0.92, respectively. Conclusions: Despite some infractions of the Rasch model, the instrument functioned well. The subscales of the MOXFQ are meaningful for assessing patient-reported complaints and outcomes in orthopaedic foot and ankle population. (C) 2020 European Foot and Ankle Society. Published by Elsevier Ltd. All rights reserved.Peer reviewe

Interobserver reproducibility of perineural invasion of prostatic adenocarcinoma in needle biopsies

Numerous studies have shown a correlation between perineural invasion (PNI) in prostate biopsies and outcome. The reporting of PNI varies widely in the literature. While the interobserver variability of prostate cancer grading has been studied extensively, less is known regarding the reproducibility of PNI. A total of 212 biopsy cores from a population-based screening trial were included in this study (106 with and 106 without PNI according to the original pathology reports). The glass slides were scanned and circulated among four pathologists with a special interest in urological pathology for assessment of PNI. Discordant cases were stained by immunohistochemistry for S-100 protein. PNI was diagnosed by all four observers in 34.0% of cases, while 41.5% were considered to be negative for PNI. In 24.5% of cases, there was a disagreement between the observers. The kappa for interobserver variability was 0.67-0.75 (mean 0.73). The observations from one participant were compared with data from the original reports, and a kappa for intraobserver variability of 0.87 was achieved. Based on immunohistochemical findings among discordant cases, 88.6% had PNI while 11.4% did not. The most common diagnostic pitfall was the presence of bundles of stroma or smooth muscle. It was noted in a few cases that collagenous micronodules could be mistaken for a nerve. The distance between cancer and nerve was another cause of disagreement. Although the results suggest that the reproducibility of PNI may be greater than that of prostate cancer grading, there is still a need for improvement and standardization

Asbestipurkutyön turvallisuuden ja siihen liittyvien testaus- ja mittaustoimintojen kehittäminen : AsbTest

Tutkimuksessa kehitettiin ja ohjeistettiin sellaisia asbestipurkutyön turvallisuuden mittaus- ja valvontakäytäntöjä, joiden avulla työntekijöiden ja muiden ihmisten asbestialtistuminen voidaan ennaltaehkäistä. Hankkeessa kehitetyillä ja testatuilla mittausmenetelmillä voidaan todentaa osastoinnin, ilmankäsittelylaitteiden ja hengityksensuojainten toimivuus. Turvallisessa asbestipurkutyössä yksikään riskinhallintamenetelmä ei saa pettää ja niiden tehokkuutta tulee seurata mittauksin. Tutkimuksen tulosten pohjalta laadittiin malliratkaisut altistumisen ehkäisemiseksi. Tuloksia voidaan soveltaa myös kaikessa muussa korjausrakentamisessa, jossa ilmaan vapautuu terveydelle haitallisia tai vaarallisia altisteita

Artificial intelligence for diagnosis and Gleason grading of prostate cancer: The PANDA challenge

Through a community-driven competition, the PANDA challenge provides a curated diverse dataset and a catalog of models for prostate cancer pathology, and represents a blueprint for evaluating AI algorithms in digital pathology. Artificial intelligence (AI) has shown promise for diagnosing prostate cancer in biopsies. However, results have been limited to individual studies, lacking validation in multinational settings. Competitions have been shown to be accelerators for medical imaging innovations, but their impact is hindered by lack of reproducibility and independent validation. With this in mind, we organized the PANDA challenge-the largest histopathology competition to date, joined by 1,290 developers-to catalyze development of reproducible AI algorithms for Gleason grading using 10,616 digitized prostate biopsies. We validated that a diverse set of submitted algorithms reached pathologist-level performance on independent cross-continental cohorts, fully blinded to the algorithm developers. On United States and European external validation sets, the algorithms achieved agreements of 0.862 (quadratically weighted kappa, 95% confidence interval (CI), 0.840-0.884) and 0.868 (95% CI, 0.835-0.900) with expert uropathologists. Successful generalization across different patient populations, laboratories and reference standards, achieved by a variety of algorithmic approaches, warrants evaluating AI-based Gleason grading in prospective clinical trials.KWF Kankerbestrijding ; Netherlands Organization for Scientific Research (NWO) ; Swedish Research Council European Commission ; Swedish Cancer Society ; Swedish eScience Research Center ; Ake Wiberg Foundation ; Prostatacancerforbundet ; Academy of Finland ; Cancer Foundation Finland ; Google Incorporated ; MICCAI board challenge working group ; Verily Life Sciences ; EIT Health ; Karolinska Institutet ; MICCAI 2020 satellite event team ; ERAPerMe

Meego-sovelluksen suunnittelu ja ohjelmointi : CASE: EKG-pitkäaikaisrekisteröinnin päiväkirja

Tiivistelmä Opinnäytetyön tavoitteena oli suunnitella ja luoda matkapuhelimeen päiväkirjasovellus EKG-pitkäaikaisrekisteröinnin avuksi. Työssä käytettiin Linux-käyttöjärjestelmään pohjautuvaa matkapuhelinta. Opinnäytetyössä kuvataan ohjelmistokehityksen eri vaiheita ja valintoja sekä käytettyjä työvälineitä Meego-käyttöjärjestelmälle ohjelmoitaessa. Työssä kuvataan myös käyttöliittymän rakentamista QML-ohjelmointikielellä. Lisäksi pyritään ottamaan huomioon käytettävyys sovelluksen käyttötarkoitusta ajatellen sekä matkapuhelimeen liittyvät erityispiirteet ohjelmaa suunniteltaessa ja ohjelmoitaessa. Sovellus ohjelmoitiin Meego-käyttöjärjestelmälle käyttäen Qt Quick -kehitysympäristöä. Ohjelmointikielinä käytettiin QML- ja Javascript-ohjelmointikieliä. Työtä voidaan hyödyntää erityisesti QML-kielisessä ohjelmistoprojekteissa, mutta myös yleisesti mobiilisovellusten suunnittelussa.Abstract The purpose of thesis was to design and create diary application to help long-term ECG registration on a Linux-based mobile phone. This thesis describes the different stages of and choices made during software development and the development tools that were used while programming for a Meego operating system. This thesis also describes user interface programming with QML -programming language. Usability from the viewpoint of the use of the application and special characteristics of the mobile phone were also consider in development. The application was programmed for Meego operating system by using Qt Quick framework and QML and Javascript languages. This thesis can be applied in particular in QML software development but also generally for designing mobile applications