These studies demonstrate that r(20) is molecularly heterogeneous and formed by two distinct mechanisms, which, in turn, produce different phenotypic spectrums.

Background Clinical prediction models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision making and individualize care. For patients with cardiovascular disease (CVD) there are numerous CPMs available though the extent of this literature is not well described. Methods and Results We conducted a systematic review for articles containing CPMs for CVD published between January 1990 through May 2012. CVD includes coronary heart disease (CHD), heart failure (HF), arrhythmias, stroke, venous thromboembolism (VTE) and peripheral vascular disease (PVD). We created a novel database and characterized CPMs based on the stage of development, population under study, performance, covariates, and predicted outcomes. There are 796 models included in this database. The number of CPMs published each year is increasing steadily over time. 717 (90%) are de novo CPMs, 21 (3%) are CPM recalibrations, and 58 (7%) are CPM adaptations. This database contains CPMs for 31 index conditions including 215 CPMs for patients with CAD, 168 CPMs for population samples, and 79 models for patients with HF. There are 77 distinct index/ outcome (I/O) pairings. Of the de novo models in this database 450 (63%) report a c-statistic and 259 (36%) report some information on calibration. Conclusions There is an abundance of CPMs available for a wide assortment of CVD conditions, with substantial redundancy in the literature. The comparative performance of these models, the consistency of effects and risk estimates across models and the actual and potential clinical impact of this body of literature is poorly understood.

Background: Clinical prediction models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision making and individualize care. For patients with cardiovascular disease (CVD) there are numerous CPMs available though the extent of this literature is not well described. Methods and Results: We conducted a systematic review for articles containing CPMs for CVD published between January 1990 through May 2012. CVD includes coronary artery disease (CAD), congestive heart failure (CHF), arrhythmias, stroke, venous thromboembolism (VTE) and peripheral vascular disease (PVD). We created a novel database and characterized CPMs based on the stage of development, population under study, performance, covariates, and predicted outcomes. We included articles that describe newly developed CPMs that predict the risk of developing an outcome (prognostic models) or the probability of a specific diagnosis (diagnostic models). There are 796 models included in this database representing 31 distinct index conditions. 717 (90%) are de novo CPMs, 21 (3%) are CPM recalibrations, and 58 (7%) are CPM adaptations. There are 215 CPMs for patients with CAD, 168 CPMs for population samples at risk for incident CVD, and 79 models for patients with CHF (Figure). De novo CPMs predicting mortality were most commonly published for patients with known CAD (98 models) followed by HF (63 models) and stroke (24 models). There are 77 distinct index/ outcome (I/O) pairings and models are roughly evenly split between those predicting short term outcomes (< 3 months) and those predicting long term outcomes (< 6 months). There are 41 diagnostic CPMs included in this database, most commonly predicting diagnoses of CAD (11 models), VTE (10 models), and acute coronary syndrome (5 models). Of the de novo models in this database 450 (63%) report a c-statistic and 259 (36%) report either the Hosmer-Lemeshow statistic or show a calibration plot. Conclusions: There is an abundance of CPMs available for many CVD conditions, with substantial redundancy in the literature. The comparative performance of these models, the consistency of effects and risk estimates across models and the actual and potential clinical impact of this body of literature is poorly understood.

Background: Gymnastics is a unique sport that places significant loads across the growing elbow, resulting in unique overuse injuries, some of which are poorly described in the current literature. Purpose: To provide a comprehensive review of the unique overuse elbow injuries seen in youth gymnasts and to provide an up-to-date synthesis of the available literature and clinical expertise guiding treatment decisions in this population. Study Design: Narrative review. Methods: A review of the PubMed database was performed to include all studies describing elbow biomechanics during gymnastics, clinical entities of the elbow in gymnasts, and outcomes of operative and/or nonoperative treatment of elbow pathology in gymnasts. Results: Participation in gymnastics among youth athletes is high, being the sixth most common sport in children. Early specialization is the norm in this sport, and gymnastics also has the highest number of participation hours of all youth sports. As a result, unique overuse elbow injuries are common, primarily on the lateral side of the elbow. Beyond common diagnoses of radiocapitellar plica and osteochondritis dissecans of the capitellum, we describe a pathology unique to gymnasts involving stress fracture of the radial head. Additionally, we synthesized our clinical experience and expertise in gymnastics to provide a sport-specific rehabilitation program that can be used by providers treating surgical and nonsurgical conditions of the elbow and wishing to provide detailed activity instructions to their athletes. Conclusion: Overuse injuries of the elbow are common in gymnastics and include osteochondritis dissecans of the capitellum, radiocapitellar plica syndrome, and newly described radial head stress fractures. A thorough understanding of the psychological, cultural, and biomechanical aspects of gymnastics are necessary to care for these athletes.

Review of Moore, Jennifer, Adam Rountrey, and Hannah Scates Kettler, eds., 3D Data Creation to Curation: Community Standards for 3D Data Preservation. Chicago, Illinois: Association of College and Research Libraries, 2022.

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Review of Hervieux, S. & Wheatley, A. (Eds.). (200). The Rise of AI: Implications and Applications of Artificial Intelligence in Academic Libraries. Chicago, IL: Association of College and Research Libraries.