Study protocol for a randomised controlled trial evaluating the benefits from bimodal solution with cochlear implant and hearing aid versus bilateral hearing aids in patients with asymmetric speech identification scores.

INTRODUCTION: Cochlear implant (CI) and hearing aid (HA) in a bimodal solution (CI+HA) is compared with bilateral HAs (HA+HA) to test if the bimodal solution results in better speech intelligibility and self-reported quality of life. METHODS AND ANALYSIS: This randomised controlled trial is conducted in Odense University Hospital, Denmark. Sixty adult bilateral HA users referred for CI surgery are enrolled if eligible and undergo: audiometry, speech perception in noise (HINT: Hearing in Noise Test), Speech Identification Scores and video head impulse test. All participants will receive new replacement HAs. After 1 month they will be randomly assigned (1:1) to the intervention group (CI+HA) or to the delayed intervention control group (HA+HA). The intervention group (CI+HA) will receive a CI on the ear with a poorer speech recognition score and continue using the HA on the other ear. The control group (HA+HA) will receive a CI after a total of 4 months of bilateral HA use.The primary outcome measures are speech intelligibility measured objectively with HINT (sentences in noise) and DANTALE I (words) and subjectively with the Speech, Spatial and Qualities of Hearing scale questionnaire. Secondary outcomes are patient reported Health-Related Quality of Life scores assessed with the Nijmegen Cochlear Implant Questionnaire, the Tinnitus Handicap Inventory and Dizziness Handicap Inventory. Third outcome is listening effort assessed with pupil dilation during HINT.In conclusion, the purpose is to improve the clinical decision-making for CI candidacy and optimise bimodal solutions. ETHICS AND DISSEMINATION: This study protocol was approved by the Ethics Committee Southern Denmark project ID S-20200074G. All participants are required to sign an informed consent form.This study will be published on completion in peer-reviewed publications and scientific conferences. TRIAL REGISTRATION NUMBER: NCT04919928.

Determining Plasma Protein Variation Parameters as a Prerequisite for Biomarker Studies-A TMT-Based LC-MSMS Proteome Investigation.

Specific plasma proteins serve as valuable markers for various diseases and are in many cases routinely measured in clinical laboratories by fully automated systems. For safe diagnostics and monitoring using these markers, it is important to ensure an analytical quality in line with clinical needs. For this purpose, information on the analytical and the biological variation of the measured plasma protein, also in the context of the discovery and validation of novel, disease protein biomarkers, is important, particularly in relation to for sample size calculations in clinical studies. Nevertheless, information on the biological variation of the majority of medium-to-high abundant plasma proteins is largely absent. In this study, we hypothesized that it is possible to generate data on inter-individual biological variation in combination with analytical variation of several hundred abundant plasma proteins, by applying LC-MS/MS in combination with relative quantification using isobaric tagging (10-plex TMT-labeling) to plasma samples. Using this analytical proteomic approach, we analyzed 42 plasma samples prepared in doublets, and estimated the technical, inter-individual biological, and total variation of 265 of the most abundant proteins present in human plasma thereby creating the prerequisites for power analysis and sample size determination in future clinical proteomics studies. Our results demonstrated that only five samples per group may provide sufficient statistical power for most of the analyzed proteins if relative changes in abundances >1.5-fold are expected. Seventeen of the measured proteins are present in the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Biological Variation Database, and demonstrated remarkably similar biological CV's to the corresponding CV's listed in the EFLM database suggesting that the generated proteomic determined variation knowledge is useful for large-scale determination of plasma protein variations.

Deep learning detects and visualizes bleeding events in electronic health records.

BACKGROUND: Bleeding is associated with a significantly increased morbidity and mortality. Bleeding events are often described in the unstructured text of electronic health records, which makes them difficult to identify by manual inspection. OBJECTIVES: To develop a deep learning model that detects and visualizes bleeding events in electronic health records. PATIENTS/METHODS: Three hundred electronic health records with International Classification of Diseases, Tenth Revision diagnosis codes for bleeding or leukemia were extracted. Each sentence in the electronic health record was annotated as positive or negative for bleeding. The annotated sentences were used to develop a deep learning model that detects bleeding at sentence and note level. RESULTS: On a balanced test set of 1178   sentences, the best-performing deep learning model achieved a sensitivity of 0.90, specificity of 0.90, and negative predictive value of 0.90. On a test set consisting of 700 notes, of which 49 were positive for bleeding, the model achieved a note-level sensitivity of 1.00, specificity of 0.52, and negative predictive value of 1.00. By using a sentence-level model on a note level, the model can explain its predictions by visualizing the exact sentence in a note that contains information regarding bleeding. Moreover, we found that the model performed consistently well across different types of bleedings. CONCLUSIONS: A deep learning model can be used to detect and visualize bleeding events in the free text of electronic health records. The deep learning model can thus facilitate systematic assessment of bleeding risk, and thereby optimize patient care and safety.

[Intravitreal angiostatic treatment of ocular vascular diseases].

Intraocular vascular diseases like neovascular age-related macular degeneration, diabetic macular oedema and retinal vein occlusion are associated with decline in vision if left untreated. Anti-vascular endothelia growth factor (VEGF) agents originally developed for cancer treatment were the beginning of a new treatment regime for intraocular vascular diseases. Ambiguous results exist regarding adverse effects but are considered limited. In the future, anti-VEGF agents are likely to be used for treatment of proliferative diabetic retinopathy, neovascular glaucoma and premature retinopathy.

Chronic pain patients with possible co-morbid post-traumatic stress disorder admitted to multidisciplinary pain rehabilitation-a 1-year cohort study.

BACKGROUND: Although post-traumatic stress disorder (PTSD) is a common co-morbidity in chronic pain, little is known about the association between PTSD and pain in the context of chronic pain rehabilitation. OBJECTIVE: The aim of the present study was two-fold: (1) to investigate the association of a possible PTSD diagnosis with symptoms of pain, physical and mental functioning, as well as the use of opioids, and (2) to compare the outcome of multidisciplinary chronic pain rehabilitation for patients with a possible PTSD diagnosis at admission with patients without PTSD at admission. METHOD: A consecutively referred cohort of 194 patients completed a baseline questionnaire at admission covering post-traumatic stress, pain symptoms, physical and mental functioning, as well as self-reported sleep quality and cognitive difficulties. Medication use was calculated from their medical records. A total of 95 were admitted to further multidisciplinary treatment and included in the outcome study. RESULTS: A high prevalence of possible PTSD was found (26.3%). Patients with possible co-morbid PTSD experienced significantly poorer general and mental health, poorer sleep quality, and more cognitive problems as well as inferior social functioning compared to patients without PTSD. Possible co-morbid PTSD did not result in higher use of opioids or sedatives. Surprisingly, possible co-morbid PTSD at admission was not associated with lower levels of symptom reduction from pre- to post-treatment. CONCLUSIONS: Possible co-morbid PTSD in chronic pain is a major problem associated with significantly poorer functioning on several domains. Nevertheless, our results indicate that pain-related symptoms could be treated with success despite possible co-morbid PTSD. However, since PTSD was only measured at admission it is not known whether rehabilitation actually reduced PTSD.