Real-World Data in Greece: Mapping the Papageorgiou General Hospital Data to the OMOP Common Data Model.

This paper showcases the results of the Extract-Transform-Load process mapping the Electronic Health Record of Papageorgiou General Hospital in Thessaloniki, Greece, to the Observational Medical Outcomes Partnership Common Data Model. We describe the staged process utilized to account for the intricate structure of the database, along with some general findings from the mapping. Finally, we investigate potential directions for future research.

Estimating individualized treatment effects from randomized controlled trials: a simulation study to compare risk-based approaches.

Background: Baseline outcome risk can be an important determinant of absolute treatment benefit and has been used in guidelines for "personalizing" medical decisions. We compared easily applicable risk-based methods for optimal prediction of individualized treatment effects.

Methods: We simulated RCT data using diverse assumptions for the average treatment effect, a baseline prognostic index of risk, the shape of its interaction with treatment (none, linear, quadratic or non-monotonic), and the magnitude of treatment-related harms (none or constant independent of the prognostic index).

Use of unstructured text in prognostic clinical prediction models: a systematic review.

Objective: This systematic review aims to assess how information from unstructured text is used to develop and validate clinical prognostic prediction models. We summarize the prediction problems and methodological landscape and determine whether using text data in addition to more commonly used structured data improves the prediction performance.

Materials And Methods: We searched Embase, MEDLINE, Web of Science, and Google Scholar to identify studies that developed prognostic prediction models using information extracted from unstructured text in a data-driven manner, published in the period from January 2005 to March 2021.

Trends in the conduct and reporting of clinical prediction model development and validation: a systematic review.

Objectives: This systematic review aims to provide further insights into the conduct and reporting of clinical prediction model development and validation over time. We focus on assessing the reporting of information necessary to enable external validation by other investigators.

Materials And Methods: We searched Embase, Medline, Web-of-Science, Cochrane Library, and Google Scholar to identify studies that developed 1 or more multivariable prognostic prediction models using electronic health record (EHR) data published in the period 2009-2019.

COVID outcome prediction in the emergency department (COPE): using retrospective Dutch hospital data to develop simple and valid models for predicting mortality and need for intensive care unit admission in patients who present at the emergency department with suspected COVID-19.

Objectives: Develop simple and valid models for predicting mortality and need for intensive care unit (ICU) admission in patients who present at the emergency department (ED) with suspected COVID-19.

Design: Retrospective.

Setting: Secondary care in four large Dutch hospitals.

Predictive approaches to heterogeneous treatment effects: a scoping review.

Background: Recent evidence suggests that there is often substantial variation in the benefits and harms across a trial population. We aimed to identify regression modeling approaches that assess heterogeneity of treatment effect within a randomized clinical trial.

Methods: We performed a literature review using a broad search strategy, complemented by suggestions of a technical expert panel.

The EORTC-DeCOG nomogram adequately predicts outcomes of patients with sentinel node-positive melanoma without the need for completion lymph node dissection.

Purpose: Based on recent advances in the management of patients with sentinel node (SN)-positive melanoma, we aimed to develop prediction models for recurrence, distant metastasis (DM) and overall mortality (OM).

Methods: The derivation cohort consisted of 1080 patients with SN-positive melanoma from nine European Organization for Research and Treatment of Cancer (EORTC) centres. Prognostic factors for recurrence, DM and OM were studied with Cox regression analysis.

Disease misclassification in electronic healthcare database studies: Deriving validity indices-A contribution from the ADVANCE project.

There is a strong and continuously growing interest in using large electronic healthcare databases to study health outcomes and the effects of pharmaceutical products. However, concerns regarding disease misclassification (i.e.

Effects of pregnancy and short-lasting acute feed restriction on total ghrelin concentration and metabolic parameters in dairy cattle.

The aims of this study were: to compare total ghrelin concentration throughout pregnancy between lactating cows and heifers, and to study the response to acute feed restriction in pregnant or non-pregnant heifers. Blood samples were collected each month of pregnancy from cows (n = 5) and heifers (n = 5) and analyzed for total ghrelin concentration. Compared to pre-conception values, ghrelin concentrations tended to be greater during 3rd month of pregnancy in heifers, whereas they were higher in the 7th, 8th and 9th months in lactating cows, but no difference was detected between lactating cows and heifers.